Bibliographic record
Abstract
Поскольку в биофармацевтической отрасли постоянный масштабный рост производства выходит из моды, необходимо наряду с модернизацией уже устаревших подходов применять и инновационные. В статье сделан обзор состояния технологической базы для проведения «даун-стрим» процесса и рассмотрены потенциально возможные решения. Список ссылок Gottschalk U. / Biopharm. Intl Suppl.. 2006. V. 19. P. 8–9. Hacker D.L., Jesus M. De, and Wurm F.M. / Biotechnol. Adv. 2009. V. 27. P. 1023–1027. Rathore A.S. and Winkle H. / Nat. Biotechnol. 2009. V. 27. P. 26–34. Berthold W., Proceeds. of BioManufacturing World. --- Shanghai, China, 2010. Wurm F.M. / Nature. 2004. V. 22. P. 1393–1398. Aldridge S. / GEN. 2006. V. 26. № 1. Pharmaceutical cGMPs for the 21st Century: A Risk-Based Approach. / FDA. --- Rockville, MD, August 2002. PAT Guidance for Industry: A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance / FDA. --- Rockville, MD, September 2004. Thiel K.A. / Nat. Biotechnol. 2004. V. 22. P. 1365–1372. Sheridan C. / Nat. Biotechnol. 2010. V. 28. P. 307–310. Walsh G. / Nat. Biotechnol. 2010. V. 28. P. 917–924. Gottschalk U. / BioPharm. Intl. Suppl. 2005. V. 18. № 3. P. 24–28. S. Vedantham V. G. and Hubbard B. / Process Scale. Purification of Antibodies, U. Gottschalk (ed.). --- NY: Wiley, 2009. P. 79–102. Glynn J. et al / Biopharm. Intl. Suppl. 2009. V.22. P.15-19. Glynn J. et al., Development of a MAb harvest protocol. Biochemical Engineering XV: Engineering Biology from Biomolecules to Complex Systems. --- Quebec City, Canada, July 15-19 2007. Thommes J. and Etzel M. / Biotechnol. Prog. 2007. V. 23. P. 42-45. Thommes J. and Gottschalk U / Process Scale Purification of Antibodies, U. Gottschalk (ed.). --- NY: Wiley, 2009. P. 293–308. Shulka A.A. and Kandula J.R / Ibid. P. 53–78. Shpritzer R. et al., 232nd ACS National Meeting. --- San Francisco CA, 2006. Glynn J / Process Scale Purification of Antibodies, U. Gottschalk (ed.). --- NY: Wiley, 2009. P. 309–324. Przybycien T., Narahari S., and Steele L. / Biotechnol. 2004. V. 15. P. 469–478. Kent U. / Meth. Mol. Biol. 1999. V. 115. P. 11–18. Page M. and Thorpe R / The Protein Protocols Handbook, 2nd ed., J.M. Walker (ed.). --- Totowa, NJ: Humana Press, 2002. P. 983–984. Lebing W. et al. / Vox Sanguinis. 2003. V. 84. P. 193–201. Parkkinen J. et al. / Vox Sanguinis. 2006. V. 90. P. 97–104. Klyushnichenko V. / Curr. Opin. Drug. Disc. Dev. 2003. V. 6. P. 848–854. Yang et al. M.X. / Proc. Natl. Acad. Sci. USA. 2003. V. 100. P. 6934–6939. Peters J., Minuth T., and Schroder W. / Protein Expr. Purif. 2005. V. 39. P. 43–53. Curling J. and Gottschalk U. / BioPharm. Intl. 2007. V. 21. P. 70–94 Gottschalk U. / Adv. Biochem. Eng. Biotechnol. 2010. V. 115. P. 171-183 Walter J.K. et al. / Protein Purification: Principles, High Resolution Methods, and Applications, 3rd ed., J.C. Janson (ed.). --- NY: Wiley, 2011. Gottschalk U. / Biotechnol. Prog. 2008. V. 24. P. 496-503. Zhou J. and Tressel T. / Biotechnol. Prog. 2006. V. 22. P. 341–349. Thommes J. and Kula M.R. / Biotechnol. Prog. 1995. V. 11. P. 357–367. Fraud N. et al., BioPharm. Intl. 2009. V. 23. P. 24–27. Faber R., Yang Y., and Gottschalk U., BioPharm. Intl. 2009. V. 23. P. 11–14. Giovannoni L., Ventani M., and Gottschalk U., BioPharm. Intl. 2009. V. 23. № 3. Curtis S. et al. / Biotechnol. Bioeng. 2003. V. 84. P. 179–186. Norling L. / J. Chromatogr. 2005. V. 1069. P. 79–89.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.014 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".