Most drugs never leave the laboratory as a result of failure to predict efficacy and safety. In response, this book offers readers an array of new and emerging technologies. These technologies arm pharmaceutical scientists with more systematic and effective approaches for deciphering the complex interactions among chemistry, biology, and medicine, helping to ensure that more research efforts focus on drugs that can be successfully translated from the laboratory to the clinic and onto the market. Among the topics addressed in Drug Efficacy, Safety, and Biologics Discovery are:
- High throughput protein–based technologies and computational models for drug development, efficacy, toxicity, systems pharmacology, biomarkers, biomolecular networks, computational systems biology modeling of dosimetry, cellular response pathways, nanotechnology to improve drug delivery, and modeling efficacy and safety of engineered biologics
Each of the fourteen chapters has been authored by one or more of the leading experts in the field. Their advice is not only based on a thorough review of the latest findings, but also their own firsthand experience in drug discovery and development. Extensive references guide readers to the literature for more in–depth investigations of particular topics.
By cutting across the many disciplines needed for successful drug discovery, this book suits the needs of all chemists, biologists, and technologists involved in drug discovery and development. Moreover, by advocating for cross–disciplinary collaboration, this book is certain to fuel future innovation in drug discovery.
PART I: DRUG EFFICACY AND SAFETY TECHNOLOGY.
1. Focus on Fundamentals: Towards Better Therapeutic Index Prediction (Jinghai J. Xu and Li J. Yu).
2. High–Throughput Protein–Based Technologies and Computational Models for Drug Development, Efficacy and Toxicity (Leonidas G. Alexopoulos, Julio Saez–Rodriguez and Christopher W. Espelin).
3. Cellular Systems Biology Applied to Pre–Clinical Safety Testing: A Case Study of CellCiphrTM Profiling (Lawrence Vernetti, William Irwin, Kenneth A. Giuliano, Albert Gough, Kate Johnston and D. Lansing Taylor).
4. Systems Pharmacology, Biomarkers and Biomolecular Networks (Aram Adourian, Thomas N. Plasterer, Raji Balasubramanian, Ezra Jennings, Shunguang Wang, Jan van der Greef, Robert McBurney, Pieter Muntendam, and Noubar Afeyan).
5. Zebrafish Models for Human Diseases and Drug Discovery (Hanbing Zhong, Ning–Ai Liu and Shuo Lin).
6. Toxicity Pathways and Models: Mining for Potential Side Effects (Sean Ekins and Josef Scheiber).
7. Computational Systems Biology Modeling of Dosimetry and Cellular Response Pathways (Qiang Zhang, Yu–Mei Tan, Sudin Bhattacharya and Melvin E. Andersen).
8. Stem Cell Technology for Embryotoxicity, Cardiotoxicity and Hepatotoxicity Evaluation (Julio C. Davila, Donald B. Stedman, Sandra J. Engle, Howard I. Pryor II and Joseph P. Vacanti).
9. Telemetry Technology for Preclinical Drug Discovery and Development (Yi Yang).
PART II. BIOLOGICS TECHNOLOGY.
10. Nanotechnology to Improve Oral Drug Delivery (Mayank D. Bhavsar, Shardool Jain, and Mansoor M. Amiji).
11. Functional Glycomics and the Future of Glycomic Drugs (Ram Sasisekharan).
12. Modeling Efficacy and Safety of Engineered Biologics (Jeff Chabot and Bruce Gomes).
13. Regulation of Gene Expression by Small, Non–Coding RNAs: Practical Applications (Roman Herrara and Eric Tien).
PART III. FUTURE PERSPECTIVE.
14. Future Perspectives of Biological Engineering in Pharmaceutical Research: The Paradigm of Modeling, Mining, Manipulation and Measurements (Jinghai J. Xu, Sean Ekins, Michael McGlashen and Douglas Lauffenburger).
Sean Ekins, MSc, PHD, DSc, is the Principal at Collaborations in Chemistry; and Adjunct Associate Professor in the Department of Pharmaceutical Sciences at the University of Maryland, School of Pharmacy. Dr. Ekins has published widely on ADME/Tox, systems biology, computational, and in vitro drug discovery approaches. He has previously edited two Wiley books: Computer Applications in Pharmaceutical Research and Development (2006) and Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals (2007).
Jinghai J. Xu, PHD, is Director of Automated Biotechnology at Merck. Previously he headed predictive toxicology at Pfizer, where he led research activities in drug–induced liver injury, genetic toxicology, drug transporters, assay development, high content screening, in vitro in vivo correlations, systems biology, and systems toxicology. Dr. Xu has served on steering committees of academic–industry and industry–industry collaborations, and as a guest lecturer at the Massachusetts Institute of Technology.