This reference describes applications of computational and molecular modeling techniques toward more efficient and affordable biopharmaceutical drug development at the pre-clinical stages that could positively impact clinical outcomes. With a primary focus on the developability of monoclonal antibody candidates, it addresses many contributions that computation can make towards biopharmaceutical drug development in general. It is a rich source of information on current principles and practices and provides a starting point for finding innovative applications of computation in biotherapeutics.
This reference describes applications of computational and molecular modeling techniques toward more efficient and affordable biopharmaceutical drug development at the pre-clinical stages that could positively impact clinical outcomes. With a primary focus on the developability of monoclonal antibody candidates, it addresses many contributions that computation can make towards biopharmaceutical drug development in general. It is a rich source of information on current principles and practices and provides a starting point for finding innovative applications of computation in biotherapeutics.
Sandeep Kumar, PhD, is a senior principal scientist at Pfizer, Inc. in the Biotherapeutics Pharmaceutical Sciences group, working on computational modeling and developability risk assessments of a wide variety of biotherapeutic drug candidates, including monoclonal antibodies, antibody-based therapeutics, fusion proteins, vaccines, and antibody-drug conjugates. He earned his PhD in computational biophysics from the Molecular Biophysics Unit of the Indian Institute of Science, Bangalore, India, and performed postdoctoral research on proteins at the National Cancer Institute in Frederick, Maryland, a part of the National Institutes of Health. He has been an assistant professor (research-track) at Georgetown University Medical Center, Washington, DC; an assistant professor at the Indian Institute of Technology, Kanpur; and an associate research scientist at Johns Hopkins University, Baltimore, Maryland. He has more than 17 years of experience in computational protein sciences. He has contributed more than 60 research papers, review articles, and book chapters, has delivered more than 40 invited talks, and has chaired sessions of several conferences. He has won several fellowships and awards, including a Fogarty visiting scientist fellowship at NIH and the 2014 Ebert Prize from the American Pharmacists Association. He has also mentored several graduate students and postdoctoral scientists. Satish Kumar Singh, PhD, is a research fellow at Pfizer, Inc. in the Biotherapeutics Pharmaceutical Sciences group, and an adjunct professor of the Department of Physical Pharmaceutical Chemistry at Uppsala University in Sweden. His responsibilities include leading formulation, product, and process development activities for biologics and therapeutic vaccines. He earned his PhD in chemical engineering from Kansas State University. He has more than 25 years of industrial experience and has published more than 50 peer-reviewed articles with emphasis on the colloidal and physical chemistry of macromolecules. He also holds four patents. He is involved in several professional groups through the American Association of Pharmaceutical Scientists and the USP, was chair of the Protein Aggregation and Immunogenicity Focus group, and is a frequently invited speaker at various conferences and symposia.
Inhaltsangabe
PRINCIPLES OF BIOPHARMACEUTICAL INFORMATICS. Biopharmaceutical Informatics: Applications of Computation in Biologic Drug Development. Computational Methods in the Optimization of Biologic Modalities. Understanding, Predicting, and Mitigating the Impact of Posttranslational Physiochemical Modifications, Including Aggregation, on the Stability of Biopharmaceutical Drug Products. Preclinical Immunogenicity Risk Assessment of Biotherapeutics. Application of Mechanistic Pharmacokinetic-Pharmacodynamic Modeling toward the Development of Biologics. Challenges in High-Concentration Biopharmaceutical Drug Delivery: A Modeling Perspective. DEVELOPABILITY PRACTICES IN THE BIOPHARMACEUTICAL INDUSTRY. Best Practices in Assessment of Developability of Biopharmaceutical Candidates. Best Practices in Developability Assessments of Therapeutic Protein Candidates in the Biopharmaceutical Industry. Best Practices in Assessing the Developability of Biopharmaceutical Candidates. Developability Assessment Workflows to De-Risk Biopharmaceutical Development.
PRINCIPLES OF BIOPHARMACEUTICAL INFORMATICS. Biopharmaceutical Informatics: Applications of Computation in Biologic Drug Development. Computational Methods in the Optimization of Biologic Modalities. Understanding, Predicting, and Mitigating the Impact of Posttranslational Physiochemical Modifications, Including Aggregation, on the Stability of Biopharmaceutical Drug Products. Preclinical Immunogenicity Risk Assessment of Biotherapeutics. Application of Mechanistic Pharmacokinetic-Pharmacodynamic Modeling toward the Development of Biologics. Challenges in High-Concentration Biopharmaceutical Drug Delivery: A Modeling Perspective. DEVELOPABILITY PRACTICES IN THE BIOPHARMACEUTICAL INDUSTRY. Best Practices in Assessment of Developability of Biopharmaceutical Candidates. Best Practices in Developability Assessments of Therapeutic Protein Candidates in the Biopharmaceutical Industry. Best Practices in Assessing the Developability of Biopharmaceutical Candidates. Developability Assessment Workflows to De-Risk Biopharmaceutical Development.
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