Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies
Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as i...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lee, Jeong Hee [verfasserIn] Khee-Su, Bae [verfasserIn] Lee, Joon Woo [verfasserIn] In, Youngyong [verfasserIn] Kwon, Taehoon [verfasserIn] Lee, Wangwoo [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Journal of open innovation - Basel : MDPI, 2015, 2(2016), 21, Seite 1-10 |
|---|---|
| Übergeordnetes Werk: |
volume:2 ; year:2016 ; number:21 ; pages:1-10 |
| Links: |
|---|
| DOI / URN: |
10.1186/s40852-016-0047-7 |
|---|
| Katalog-ID: |
87782116X |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | 87782116X | ||
| 003 | DE-627 | ||
| 005 | 20230710100209.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 170125s2016 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1186/s40852-016-0047-7 |2 doi | |
| 024 | 7 | |a 10419/176533 |2 hdl | |
| 035 | |a (DE-627)87782116X | ||
| 035 | |a (DE-599)GBV87782116X | ||
| 035 | |a (DE-He213)s40852-016-0047-7-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 100 | 1 | |a Lee, Jeong Hee |e verfasserin |0 (DE-588)1124100814 |0 (DE-627)877821364 |0 (DE-576)48229874X |4 aut | |
| 245 | 1 | 0 | |a Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies |c Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. | ||
| 700 | 1 | |a Khee-Su, Bae |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Joon Woo |e verfasserin |0 (DE-588)1124101349 |0 (DE-627)877822255 |0 (DE-576)482299274 |4 aut | |
| 700 | 1 | |a In, Youngyong |e verfasserin |0 (DE-588)1124101578 |0 (DE-627)877822697 |0 (DE-576)482299886 |4 aut | |
| 700 | 1 | |a Kwon, Taehoon |e verfasserin |0 (DE-588)112410173X |0 (DE-627)877822921 |0 (DE-576)482299819 |4 aut | |
| 700 | 1 | |a Lee, Wangwoo |e verfasserin |0 (DE-588)1124101756 |0 (DE-627)877822980 |0 (DE-576)482299797 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of open innovation |d Basel : MDPI, 2015 |g 2(2016), 21, Seite 1-10 |h Online-Ressource |w (DE-627)833526413 |w (DE-600)2832108-X |w (DE-576)444393463 |x 2199-8531 |7 nnns |
| 773 | 1 | 8 | |g volume:2 |g year:2016 |g number:21 |g pages:1-10 |
| 856 | 4 | 0 | |u http://hdl.handle.net/10419/176533 |x Resolving-System |3 Volltext |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1186/s40852-016-0047-7 |x Resolving-System |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ILN_26 | ||
| 912 | |a ISIL_DE-206 | ||
| 912 | |a SYSFLAG_1 | ||
| 912 | |a GBV_KXP | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_170 | ||
| 912 | |a GBV_ILN_206 | ||
| 912 | |a GBV_ILN_213 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_230 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_2001 | ||
| 912 | |a GBV_ILN_2003 | ||
| 912 | |a GBV_ILN_2005 | ||
| 912 | |a GBV_ILN_2006 | ||
| 912 | |a GBV_ILN_2007 | ||
| 912 | |a GBV_ILN_2008 | ||
| 912 | |a GBV_ILN_2009 | ||
| 912 | |a GBV_ILN_2010 | ||
| 912 | |a GBV_ILN_2011 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_2015 | ||
| 912 | |a GBV_ILN_2020 | ||
| 912 | |a GBV_ILN_2021 | ||
| 912 | |a GBV_ILN_2025 | ||
| 912 | |a GBV_ILN_2026 | ||
| 912 | |a GBV_ILN_2027 | ||
| 912 | |a GBV_ILN_2034 | ||
| 912 | |a GBV_ILN_2038 | ||
| 912 | |a GBV_ILN_2044 | ||
| 912 | |a GBV_ILN_2048 | ||
| 912 | |a GBV_ILN_2049 | ||
| 912 | |a GBV_ILN_2050 | ||
| 912 | |a GBV_ILN_2055 | ||
| 912 | |a GBV_ILN_2056 | ||
| 912 | |a GBV_ILN_2059 | ||
| 912 | |a GBV_ILN_2061 | ||
| 912 | |a GBV_ILN_2064 | ||
| 912 | |a GBV_ILN_2088 | ||
| 912 | |a GBV_ILN_2106 | ||
| 912 | |a GBV_ILN_2110 | ||
| 912 | |a GBV_ILN_2112 | ||
| 912 | |a GBV_ILN_2122 | ||
| 912 | |a GBV_ILN_2129 | ||
| 912 | |a GBV_ILN_2143 | ||
| 912 | |a GBV_ILN_2152 | ||
| 912 | |a GBV_ILN_2153 | ||
| 912 | |a GBV_ILN_2190 | ||
| 912 | |a GBV_ILN_2232 | ||
| 912 | |a GBV_ILN_2336 | ||
| 912 | |a GBV_ILN_2470 | ||
| 912 | |a GBV_ILN_2507 | ||
| 912 | |a GBV_ILN_4012 | ||
| 912 | |a GBV_ILN_4035 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4126 | ||
| 912 | |a GBV_ILN_4242 | ||
| 912 | |a GBV_ILN_4249 | ||
| 912 | |a GBV_ILN_4251 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4306 | ||
| 912 | |a GBV_ILN_4307 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4322 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4326 | ||
| 912 | |a GBV_ILN_4333 | ||
| 912 | |a GBV_ILN_4334 | ||
| 912 | |a GBV_ILN_4335 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4367 | ||
| 912 | |a GBV_ILN_4393 | ||
| 912 | |a GBV_ILN_4700 | ||
| 935 | |i zbwolc20170227 | ||
| 951 | |a AR | ||
| 952 | |d 2 |j 2016 |e 21 |h 1-10 | ||
| 980 | |2 26 |1 01 |x 0206 |b 1659514096 |y x1k |z 25-01-17 | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Valuation | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Licensing deal | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Drug Royalty data | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Royalty rate | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Up-front fee | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Up-front Payment | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Milestones | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Regression | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Drug class | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Anticancer | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Antineoplastics | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Attrition rate | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Development phase | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Licensee | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Life sciences | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a rNPV | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a eNPV (expected NPV) | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a DCF | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Multivariable analysis | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a IPC code | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a TCT median value | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Market Size | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a CAGR | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a IP | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Revenue | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Multiple input descriptor | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Significance level | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a P-Value | ||
| 982 | |2 26 |1 00 |x DE-206 |8 56 |a Prediction | ||
| author_variant |
j h l jh jhl b k s bks j w l jw jwl y i yi t k tk w l wl |
|---|---|
| matchkey_str |
article:21998531:2016----::automtobrgesoaayiorarylyeaedtbuigutpenudsrposnoatngtainilf |
| hierarchy_sort_str |
2016 |
| publishDate |
2016 |
| allfields |
10.1186/s40852-016-0047-7 doi 10419/176533 hdl (DE-627)87782116X (DE-599)GBV87782116X (DE-He213)s40852-016-0047-7-e DE-627 ger DE-627 rda eng Lee, Jeong Hee verfasserin (DE-588)1124100814 (DE-627)877821364 (DE-576)48229874X aut Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. Khee-Su, Bae verfasserin aut Lee, Joon Woo verfasserin (DE-588)1124101349 (DE-627)877822255 (DE-576)482299274 aut In, Youngyong verfasserin (DE-588)1124101578 (DE-627)877822697 (DE-576)482299886 aut Kwon, Taehoon verfasserin (DE-588)112410173X (DE-627)877822921 (DE-576)482299819 aut Lee, Wangwoo verfasserin (DE-588)1124101756 (DE-627)877822980 (DE-576)482299797 aut Enthalten in Journal of open innovation Basel : MDPI, 2015 2(2016), 21, Seite 1-10 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:2 year:2016 number:21 pages:1-10 http://hdl.handle.net/10419/176533 Resolving-System Volltext http://dx.doi.org/10.1186/s40852-016-0047-7 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 zbwolc20170227 AR 2 2016 21 1-10 26 01 0206 1659514096 x1k 25-01-17 26 00 DE-206 56 Valuation 26 00 DE-206 56 Licensing deal 26 00 DE-206 56 Drug Royalty data 26 00 DE-206 56 Royalty rate 26 00 DE-206 56 Up-front fee 26 00 DE-206 56 Up-front Payment 26 00 DE-206 56 Milestones 26 00 DE-206 56 Regression 26 00 DE-206 56 Drug class 26 00 DE-206 56 Anticancer 26 00 DE-206 56 Antineoplastics 26 00 DE-206 56 Attrition rate 26 00 DE-206 56 Development phase 26 00 DE-206 56 Licensee 26 00 DE-206 56 Life sciences 26 00 DE-206 56 rNPV 26 00 DE-206 56 eNPV (expected NPV) 26 00 DE-206 56 DCF 26 00 DE-206 56 Multivariable analysis 26 00 DE-206 56 IPC code 26 00 DE-206 56 TCT median value 26 00 DE-206 56 Market Size 26 00 DE-206 56 CAGR 26 00 DE-206 56 IP 26 00 DE-206 56 Revenue 26 00 DE-206 56 Multiple input descriptor 26 00 DE-206 56 Significance level 26 00 DE-206 56 P-Value 26 00 DE-206 56 Prediction |
| spelling |
10.1186/s40852-016-0047-7 doi 10419/176533 hdl (DE-627)87782116X (DE-599)GBV87782116X (DE-He213)s40852-016-0047-7-e DE-627 ger DE-627 rda eng Lee, Jeong Hee verfasserin (DE-588)1124100814 (DE-627)877821364 (DE-576)48229874X aut Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. Khee-Su, Bae verfasserin aut Lee, Joon Woo verfasserin (DE-588)1124101349 (DE-627)877822255 (DE-576)482299274 aut In, Youngyong verfasserin (DE-588)1124101578 (DE-627)877822697 (DE-576)482299886 aut Kwon, Taehoon verfasserin (DE-588)112410173X (DE-627)877822921 (DE-576)482299819 aut Lee, Wangwoo verfasserin (DE-588)1124101756 (DE-627)877822980 (DE-576)482299797 aut Enthalten in Journal of open innovation Basel : MDPI, 2015 2(2016), 21, Seite 1-10 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:2 year:2016 number:21 pages:1-10 http://hdl.handle.net/10419/176533 Resolving-System Volltext http://dx.doi.org/10.1186/s40852-016-0047-7 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 zbwolc20170227 AR 2 2016 21 1-10 26 01 0206 1659514096 x1k 25-01-17 26 00 DE-206 56 Valuation 26 00 DE-206 56 Licensing deal 26 00 DE-206 56 Drug Royalty data 26 00 DE-206 56 Royalty rate 26 00 DE-206 56 Up-front fee 26 00 DE-206 56 Up-front Payment 26 00 DE-206 56 Milestones 26 00 DE-206 56 Regression 26 00 DE-206 56 Drug class 26 00 DE-206 56 Anticancer 26 00 DE-206 56 Antineoplastics 26 00 DE-206 56 Attrition rate 26 00 DE-206 56 Development phase 26 00 DE-206 56 Licensee 26 00 DE-206 56 Life sciences 26 00 DE-206 56 rNPV 26 00 DE-206 56 eNPV (expected NPV) 26 00 DE-206 56 DCF 26 00 DE-206 56 Multivariable analysis 26 00 DE-206 56 IPC code 26 00 DE-206 56 TCT median value 26 00 DE-206 56 Market Size 26 00 DE-206 56 CAGR 26 00 DE-206 56 IP 26 00 DE-206 56 Revenue 26 00 DE-206 56 Multiple input descriptor 26 00 DE-206 56 Significance level 26 00 DE-206 56 P-Value 26 00 DE-206 56 Prediction |
| allfields_unstemmed |
10.1186/s40852-016-0047-7 doi 10419/176533 hdl (DE-627)87782116X (DE-599)GBV87782116X (DE-He213)s40852-016-0047-7-e DE-627 ger DE-627 rda eng Lee, Jeong Hee verfasserin (DE-588)1124100814 (DE-627)877821364 (DE-576)48229874X aut Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. Khee-Su, Bae verfasserin aut Lee, Joon Woo verfasserin (DE-588)1124101349 (DE-627)877822255 (DE-576)482299274 aut In, Youngyong verfasserin (DE-588)1124101578 (DE-627)877822697 (DE-576)482299886 aut Kwon, Taehoon verfasserin (DE-588)112410173X (DE-627)877822921 (DE-576)482299819 aut Lee, Wangwoo verfasserin (DE-588)1124101756 (DE-627)877822980 (DE-576)482299797 aut Enthalten in Journal of open innovation Basel : MDPI, 2015 2(2016), 21, Seite 1-10 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:2 year:2016 number:21 pages:1-10 http://hdl.handle.net/10419/176533 Resolving-System Volltext http://dx.doi.org/10.1186/s40852-016-0047-7 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 zbwolc20170227 AR 2 2016 21 1-10 26 01 0206 1659514096 x1k 25-01-17 26 00 DE-206 56 Valuation 26 00 DE-206 56 Licensing deal 26 00 DE-206 56 Drug Royalty data 26 00 DE-206 56 Royalty rate 26 00 DE-206 56 Up-front fee 26 00 DE-206 56 Up-front Payment 26 00 DE-206 56 Milestones 26 00 DE-206 56 Regression 26 00 DE-206 56 Drug class 26 00 DE-206 56 Anticancer 26 00 DE-206 56 Antineoplastics 26 00 DE-206 56 Attrition rate 26 00 DE-206 56 Development phase 26 00 DE-206 56 Licensee 26 00 DE-206 56 Life sciences 26 00 DE-206 56 rNPV 26 00 DE-206 56 eNPV (expected NPV) 26 00 DE-206 56 DCF 26 00 DE-206 56 Multivariable analysis 26 00 DE-206 56 IPC code 26 00 DE-206 56 TCT median value 26 00 DE-206 56 Market Size 26 00 DE-206 56 CAGR 26 00 DE-206 56 IP 26 00 DE-206 56 Revenue 26 00 DE-206 56 Multiple input descriptor 26 00 DE-206 56 Significance level 26 00 DE-206 56 P-Value 26 00 DE-206 56 Prediction |
| allfieldsGer |
10.1186/s40852-016-0047-7 doi 10419/176533 hdl (DE-627)87782116X (DE-599)GBV87782116X (DE-He213)s40852-016-0047-7-e DE-627 ger DE-627 rda eng Lee, Jeong Hee verfasserin (DE-588)1124100814 (DE-627)877821364 (DE-576)48229874X aut Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. Khee-Su, Bae verfasserin aut Lee, Joon Woo verfasserin (DE-588)1124101349 (DE-627)877822255 (DE-576)482299274 aut In, Youngyong verfasserin (DE-588)1124101578 (DE-627)877822697 (DE-576)482299886 aut Kwon, Taehoon verfasserin (DE-588)112410173X (DE-627)877822921 (DE-576)482299819 aut Lee, Wangwoo verfasserin (DE-588)1124101756 (DE-627)877822980 (DE-576)482299797 aut Enthalten in Journal of open innovation Basel : MDPI, 2015 2(2016), 21, Seite 1-10 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:2 year:2016 number:21 pages:1-10 http://hdl.handle.net/10419/176533 Resolving-System Volltext http://dx.doi.org/10.1186/s40852-016-0047-7 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 zbwolc20170227 AR 2 2016 21 1-10 26 01 0206 1659514096 x1k 25-01-17 26 00 DE-206 56 Valuation 26 00 DE-206 56 Licensing deal 26 00 DE-206 56 Drug Royalty data 26 00 DE-206 56 Royalty rate 26 00 DE-206 56 Up-front fee 26 00 DE-206 56 Up-front Payment 26 00 DE-206 56 Milestones 26 00 DE-206 56 Regression 26 00 DE-206 56 Drug class 26 00 DE-206 56 Anticancer 26 00 DE-206 56 Antineoplastics 26 00 DE-206 56 Attrition rate 26 00 DE-206 56 Development phase 26 00 DE-206 56 Licensee 26 00 DE-206 56 Life sciences 26 00 DE-206 56 rNPV 26 00 DE-206 56 eNPV (expected NPV) 26 00 DE-206 56 DCF 26 00 DE-206 56 Multivariable analysis 26 00 DE-206 56 IPC code 26 00 DE-206 56 TCT median value 26 00 DE-206 56 Market Size 26 00 DE-206 56 CAGR 26 00 DE-206 56 IP 26 00 DE-206 56 Revenue 26 00 DE-206 56 Multiple input descriptor 26 00 DE-206 56 Significance level 26 00 DE-206 56 P-Value 26 00 DE-206 56 Prediction |
| allfieldsSound |
10.1186/s40852-016-0047-7 doi 10419/176533 hdl (DE-627)87782116X (DE-599)GBV87782116X (DE-He213)s40852-016-0047-7-e DE-627 ger DE-627 rda eng Lee, Jeong Hee verfasserin (DE-588)1124100814 (DE-627)877821364 (DE-576)48229874X aut Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. Khee-Su, Bae verfasserin aut Lee, Joon Woo verfasserin (DE-588)1124101349 (DE-627)877822255 (DE-576)482299274 aut In, Youngyong verfasserin (DE-588)1124101578 (DE-627)877822697 (DE-576)482299886 aut Kwon, Taehoon verfasserin (DE-588)112410173X (DE-627)877822921 (DE-576)482299819 aut Lee, Wangwoo verfasserin (DE-588)1124101756 (DE-627)877822980 (DE-576)482299797 aut Enthalten in Journal of open innovation Basel : MDPI, 2015 2(2016), 21, Seite 1-10 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:2 year:2016 number:21 pages:1-10 http://hdl.handle.net/10419/176533 Resolving-System Volltext http://dx.doi.org/10.1186/s40852-016-0047-7 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 zbwolc20170227 AR 2 2016 21 1-10 26 01 0206 1659514096 x1k 25-01-17 26 00 DE-206 56 Valuation 26 00 DE-206 56 Licensing deal 26 00 DE-206 56 Drug Royalty data 26 00 DE-206 56 Royalty rate 26 00 DE-206 56 Up-front fee 26 00 DE-206 56 Up-front Payment 26 00 DE-206 56 Milestones 26 00 DE-206 56 Regression 26 00 DE-206 56 Drug class 26 00 DE-206 56 Anticancer 26 00 DE-206 56 Antineoplastics 26 00 DE-206 56 Attrition rate 26 00 DE-206 56 Development phase 26 00 DE-206 56 Licensee 26 00 DE-206 56 Life sciences 26 00 DE-206 56 rNPV 26 00 DE-206 56 eNPV (expected NPV) 26 00 DE-206 56 DCF 26 00 DE-206 56 Multivariable analysis 26 00 DE-206 56 IPC code 26 00 DE-206 56 TCT median value 26 00 DE-206 56 Market Size 26 00 DE-206 56 CAGR 26 00 DE-206 56 IP 26 00 DE-206 56 Revenue 26 00 DE-206 56 Multiple input descriptor 26 00 DE-206 56 Significance level 26 00 DE-206 56 P-Value 26 00 DE-206 56 Prediction |
| language |
English |
| source |
Enthalten in Journal of open innovation 2(2016), 21, Seite 1-10 volume:2 year:2016 number:21 pages:1-10 |
| sourceStr |
Enthalten in Journal of open innovation 2(2016), 21, Seite 1-10 volume:2 year:2016 number:21 pages:1-10 |
| format_phy_str_mv |
Article |
| building |
26:1 |
| institution |
findex.gbv.de |
| selectbib_iln_str_mv |
26@1k |
| sw_local_iln_str_mv |
26:Valuation DE-206:Valuation 26:Licensing deal DE-206:Licensing deal 26:Drug Royalty data DE-206:Drug Royalty data 26:Royalty rate DE-206:Royalty rate 26:Up-front fee DE-206:Up-front fee 26:Up-front Payment DE-206:Up-front Payment 26:Milestones DE-206:Milestones 26:Regression DE-206:Regression 26:Drug class DE-206:Drug class 26:Anticancer DE-206:Anticancer 26:Antineoplastics DE-206:Antineoplastics 26:Attrition rate DE-206:Attrition rate 26:Development phase DE-206:Development phase 26:Licensee DE-206:Licensee 26:Life sciences DE-206:Life sciences 26:rNPV DE-206:rNPV 26:eNPV (expected NPV) DE-206:eNPV (expected NPV) 26:DCF DE-206:DCF 26:Multivariable analysis DE-206:Multivariable analysis 26:IPC code DE-206:IPC code 26:TCT median value DE-206:TCT median value 26:Market Size DE-206:Market Size 26:CAGR DE-206:CAGR 26:IP DE-206:IP 26:Revenue DE-206:Revenue 26:Multiple input descriptor DE-206:Multiple input descriptor 26:Significance level DE-206:Significance level 26:P-Value DE-206:P-Value 26:Prediction DE-206:Prediction |
| isfreeaccess_bool |
false |
| container_title |
Journal of open innovation |
| authorswithroles_txt_mv |
Lee, Jeong Hee @@aut@@ Khee-Su, Bae @@aut@@ Lee, Joon Woo @@aut@@ In, Youngyong @@aut@@ Kwon, Taehoon @@aut@@ Lee, Wangwoo @@aut@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
833526413 |
| id |
87782116X |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">87782116X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230710100209.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">170125s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s40852-016-0047-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10419/176533</subfield><subfield code="2">hdl</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)87782116X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBV87782116X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s40852-016-0047-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lee, Jeong Hee</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124100814</subfield><subfield code="0">(DE-627)877821364</subfield><subfield code="0">(DE-576)48229874X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies</subfield><subfield code="c">Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Khee-Su, Bae</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lee, Joon Woo</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124101349</subfield><subfield code="0">(DE-627)877822255</subfield><subfield code="0">(DE-576)482299274</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">In, Youngyong</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124101578</subfield><subfield code="0">(DE-627)877822697</subfield><subfield code="0">(DE-576)482299886</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kwon, Taehoon</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)112410173X</subfield><subfield code="0">(DE-627)877822921</subfield><subfield code="0">(DE-576)482299819</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lee, Wangwoo</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124101756</subfield><subfield code="0">(DE-627)877822980</subfield><subfield code="0">(DE-576)482299797</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of open innovation</subfield><subfield code="d">Basel : MDPI, 2015</subfield><subfield code="g">2(2016), 21, Seite 1-10</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)833526413</subfield><subfield code="w">(DE-600)2832108-X</subfield><subfield code="w">(DE-576)444393463</subfield><subfield code="x">2199-8531</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:2</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:21</subfield><subfield code="g">pages:1-10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://hdl.handle.net/10419/176533</subfield><subfield code="x">Resolving-System</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1186/s40852-016-0047-7</subfield><subfield code="x">Resolving-System</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_26</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ISIL_DE-206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_1</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_KXP</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="935" ind1=" " ind2=" "><subfield code="i">zbwolc20170227</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">2</subfield><subfield code="j">2016</subfield><subfield code="e">21</subfield><subfield code="h">1-10</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">01</subfield><subfield code="x">0206</subfield><subfield code="b">1659514096</subfield><subfield code="y">x1k</subfield><subfield code="z">25-01-17</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Valuation</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Licensing deal</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Drug Royalty data</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Royalty rate</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Up-front fee</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Up-front Payment</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Milestones</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Regression</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Drug class</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Anticancer</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Antineoplastics</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Attrition rate</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Development phase</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Licensee</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Life sciences</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">rNPV</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">eNPV (expected NPV)</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">DCF</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Multivariable analysis</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">IPC code</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">TCT median value</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Market Size</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">CAGR</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">IP</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Revenue</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Multiple input descriptor</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Significance level</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">P-Value</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Prediction</subfield></datafield></record></collection>
|
| author |
Lee, Jeong Hee |
| spellingShingle |
Lee, Jeong Hee 26 Valuation 26 Licensing deal 26 Drug Royalty data 26 Royalty rate 26 Up-front fee 26 Up-front Payment 26 Milestones 26 Regression 26 Drug class 26 Anticancer 26 Antineoplastics 26 Attrition rate 26 Development phase 26 Licensee 26 Life sciences 26 rNPV 26 eNPV (expected NPV) 26 DCF 26 Multivariable analysis 26 IPC code 26 TCT median value 26 Market Size 26 CAGR 26 IP 26 Revenue 26 Multiple input descriptor 26 Significance level 26 P-Value 26 Prediction Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies |
| authorStr |
Lee, Jeong Hee |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)833526413 |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut aut |
| typewithnormlink_str_mv |
Person@(DE-588)1124100814 DifferentiatedPerson@(DE-588)1124100814 Person@(DE-588)1124101349 DifferentiatedPerson@(DE-588)1124101349 Person@(DE-588)1124101578 DifferentiatedPerson@(DE-588)1124101578 DifferentiatedPerson@(DE-588)112410173X Person@(DE-588)112410173X DifferentiatedPerson@(DE-588)1124101756 Person@(DE-588)1124101756 |
| collection |
KXP GVK SWB |
| remote_str |
true |
| last_changed_iln_str_mv |
26@25-01-17 |
| illustrated |
Not Illustrated |
| issn |
2199-8531 |
| topic_title |
26 00 DE-206 56 Valuation 26 00 DE-206 56 Licensing deal 26 00 DE-206 56 Drug Royalty data 26 00 DE-206 56 Royalty rate 26 00 DE-206 56 Up-front fee 26 00 DE-206 56 Up-front Payment 26 00 DE-206 56 Milestones 26 00 DE-206 56 Regression 26 00 DE-206 56 Drug class 26 00 DE-206 56 Anticancer 26 00 DE-206 56 Antineoplastics 26 00 DE-206 56 Attrition rate 26 00 DE-206 56 Development phase 26 00 DE-206 56 Licensee 26 00 DE-206 56 Life sciences 26 00 DE-206 56 rNPV 26 00 DE-206 56 eNPV (expected NPV) 26 00 DE-206 56 DCF 26 00 DE-206 56 Multivariable analysis 26 00 DE-206 56 IPC code 26 00 DE-206 56 TCT median value 26 00 DE-206 56 Market Size 26 00 DE-206 56 CAGR 26 00 DE-206 56 IP 26 00 DE-206 56 Revenue 26 00 DE-206 56 Multiple input descriptor 26 00 DE-206 56 Significance level 26 00 DE-206 56 P-Value 26 00 DE-206 56 Prediction Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee |
| topic |
26 Valuation 26 Licensing deal 26 Drug Royalty data 26 Royalty rate 26 Up-front fee 26 Up-front Payment 26 Milestones 26 Regression 26 Drug class 26 Anticancer 26 Antineoplastics 26 Attrition rate 26 Development phase 26 Licensee 26 Life sciences 26 rNPV 26 eNPV (expected NPV) 26 DCF 26 Multivariable analysis 26 IPC code 26 TCT median value 26 Market Size 26 CAGR 26 IP 26 Revenue 26 Multiple input descriptor 26 Significance level 26 P-Value 26 Prediction |
| topic_unstemmed |
26 Valuation 26 Licensing deal 26 Drug Royalty data 26 Royalty rate 26 Up-front fee 26 Up-front Payment 26 Milestones 26 Regression 26 Drug class 26 Anticancer 26 Antineoplastics 26 Attrition rate 26 Development phase 26 Licensee 26 Life sciences 26 rNPV 26 eNPV (expected NPV) 26 DCF 26 Multivariable analysis 26 IPC code 26 TCT median value 26 Market Size 26 CAGR 26 IP 26 Revenue 26 Multiple input descriptor 26 Significance level 26 P-Value 26 Prediction |
| topic_browse |
26 Valuation 26 Licensing deal 26 Drug Royalty data 26 Royalty rate 26 Up-front fee 26 Up-front Payment 26 Milestones 26 Regression 26 Drug class 26 Anticancer 26 Antineoplastics 26 Attrition rate 26 Development phase 26 Licensee 26 Life sciences 26 rNPV 26 eNPV (expected NPV) 26 DCF 26 Multivariable analysis 26 IPC code 26 TCT median value 26 Market Size 26 CAGR 26 IP 26 Revenue 26 Multiple input descriptor 26 Significance level 26 P-Value 26 Prediction |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Journal of open innovation |
| normlinkwithtype_str_mv |
(DE-588)1124100814@Person (DE-588)1124100814@DifferentiatedPerson (DE-588)1124101349@Person (DE-588)1124101349@DifferentiatedPerson (DE-588)1124101578@Person (DE-588)1124101578@DifferentiatedPerson (DE-588)112410173X@DifferentiatedPerson (DE-588)112410173X@Person (DE-588)1124101756@DifferentiatedPerson (DE-588)1124101756@Person |
| hierarchy_parent_id |
833526413 |
| hierarchy_top_title |
Journal of open innovation |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 |
| normlinkwithrole_str_mv |
(DE-588)1124100814@@aut@@ (DE-588)1124101349@@aut@@ (DE-588)1124101578@@aut@@ (DE-588)112410173X@@aut@@ (DE-588)1124101756@@aut@@ |
| title |
Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies |
| ctrlnum |
(DE-627)87782116X (DE-599)GBV87782116X (DE-He213)s40852-016-0047-7-e |
| title_full |
Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee |
| author_sort |
Lee, Jeong Hee |
| journal |
Journal of open innovation |
| journalStr |
Journal of open innovation |
| lang_code |
eng |
| isOA_bool |
false |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
txt |
| container_start_page |
1 |
| author_browse |
Lee, Jeong Hee Khee-Su, Bae Lee, Joon Woo In, Youngyong Kwon, Taehoon Lee, Wangwoo |
| selectkey |
26:x |
| container_volume |
2 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Lee, Jeong Hee |
| doi_str_mv |
10.1186/s40852-016-0047-7 |
| normlink |
1124100814 877821364 48229874X 1124101349 877822255 482299274 1124101578 877822697 482299886 112410173X 877822921 482299819 1124101756 877822980 482299797 |
| normlink_prefix_str_mv |
(DE-588)1124100814 (DE-627)877821364 (DE-576)48229874X (DE-588)1124101349 (DE-627)877822255 (DE-576)482299274 (DE-588)1124101578 (DE-627)877822697 (DE-576)482299886 (DE-588)112410173X (DE-627)877822921 (DE-576)482299819 (DE-588)1124101756 (DE-627)877822980 (DE-576)482299797 |
| author2-role |
verfasserin |
| title_sort |
valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in life science area-focused on anticancer therapies |
| title_auth |
Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies |
| abstract |
Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. |
| abstractGer |
Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. |
| abstract_unstemmed |
Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue. |
| collection_details |
GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 |
| container_issue |
21 |
| title_short |
Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies |
| url |
http://hdl.handle.net/10419/176533 http://dx.doi.org/10.1186/s40852-016-0047-7 |
| ausleihindikator_str_mv |
26 |
| rolewithnormlink_str_mv |
@@aut@@(DE-588)1124100814 @@aut@@(DE-588)1124101349 @@aut@@(DE-588)1124101578 @@aut@@(DE-588)112410173X @@aut@@(DE-588)1124101756 |
| remote_bool |
true |
| author2 |
Khee-Su, Bae Lee, Joon Woo In, Youngyong Kwon, Taehoon Lee, Wangwoo |
| author2Str |
Khee-Su, Bae Lee, Joon Woo In, Youngyong Kwon, Taehoon Lee, Wangwoo |
| ppnlink |
833526413 |
| GND_str_mv |
Jeong, Lee Jeong Lee Jeong Hee Lee, Jeong Hee Joon, Woo Lee Lee Joon Woo Lee, Joon Woo In Youngyong Youngyon, In In, Youngyong Taehoon, Kwon Kwon Taehoon Kwon, Taehoon Wangwoo, Lee Lee Wangwoo Lee, Wangwoo |
| GND_txt_mv |
Jeong, Lee Jeong Lee Jeong Hee Lee, Jeong Hee Joon, Woo Lee Lee Joon Woo Lee, Joon Woo In Youngyong Youngyon, In In, Youngyong Taehoon, Kwon Kwon Taehoon Kwon, Taehoon Wangwoo, Lee Lee Wangwoo Lee, Wangwoo |
| GND_txtF_mv |
Jeong, Lee Jeong Lee Jeong Hee Lee, Jeong Hee Joon, Woo Lee Lee Joon Woo Lee, Joon Woo In Youngyong Youngyon, In In, Youngyong Taehoon, Kwon Kwon Taehoon Kwon, Taehoon Wangwoo, Lee Lee Wangwoo Lee, Wangwoo |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1186/s40852-016-0047-7 |
| up_date |
2024-07-04T13:52:35.713Z |
| _version_ |
1803656789457108992 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">87782116X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230710100209.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">170125s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s40852-016-0047-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10419/176533</subfield><subfield code="2">hdl</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)87782116X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBV87782116X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s40852-016-0047-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lee, Jeong Hee</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124100814</subfield><subfield code="0">(DE-627)877821364</subfield><subfield code="0">(DE-576)48229874X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies</subfield><subfield code="c">Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. <Drug Class: Anticancer activity candidates> Royalty Rate=9.997+0.063 ∗ Attrition Rate+1.655 ∗ Licensee Revenue - 0.410 ∗ TCT Median -1.090 ∗ Market Size - 0.230 ∗ CAGR (Formula 1) Up-Front Payment (Up-front+Milestones)=2.909 - 0.006 ∗ Attrition Rate+0.306 ∗ Licensee Revenue - 0.74 ∗ TCT Median - 0.113 ∗ Market Size - 0.009 ∗ CAGR (Formula 2) In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. Research limitations/implications (if applicable) This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Practical implications (if applicable) Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Khee-Su, Bae</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lee, Joon Woo</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124101349</subfield><subfield code="0">(DE-627)877822255</subfield><subfield code="0">(DE-576)482299274</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">In, Youngyong</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124101578</subfield><subfield code="0">(DE-627)877822697</subfield><subfield code="0">(DE-576)482299886</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kwon, Taehoon</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)112410173X</subfield><subfield code="0">(DE-627)877822921</subfield><subfield code="0">(DE-576)482299819</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lee, Wangwoo</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1124101756</subfield><subfield code="0">(DE-627)877822980</subfield><subfield code="0">(DE-576)482299797</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of open innovation</subfield><subfield code="d">Basel : MDPI, 2015</subfield><subfield code="g">2(2016), 21, Seite 1-10</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)833526413</subfield><subfield code="w">(DE-600)2832108-X</subfield><subfield code="w">(DE-576)444393463</subfield><subfield code="x">2199-8531</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:2</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:21</subfield><subfield code="g">pages:1-10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://hdl.handle.net/10419/176533</subfield><subfield code="x">Resolving-System</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1186/s40852-016-0047-7</subfield><subfield code="x">Resolving-System</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_26</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ISIL_DE-206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_1</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_KXP</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="935" ind1=" " ind2=" "><subfield code="i">zbwolc20170227</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">2</subfield><subfield code="j">2016</subfield><subfield code="e">21</subfield><subfield code="h">1-10</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">01</subfield><subfield code="x">0206</subfield><subfield code="b">1659514096</subfield><subfield code="y">x1k</subfield><subfield code="z">25-01-17</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Valuation</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Licensing deal</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Drug Royalty data</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Royalty rate</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Up-front fee</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Up-front Payment</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Milestones</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Regression</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Drug class</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Anticancer</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Antineoplastics</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Attrition rate</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Development phase</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Licensee</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Life sciences</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">rNPV</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">eNPV (expected NPV)</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">DCF</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Multivariable analysis</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">IPC code</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">TCT median value</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Market Size</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">CAGR</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">IP</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Revenue</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Multiple input descriptor</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Significance level</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">P-Value</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="8">56</subfield><subfield code="a">Prediction</subfield></datafield></record></collection>
|
| score |
7.3997917 |