TY - BOOK ID - 14305905 TI - Pharmaco-complexity : non-linear phenomena and drug product development AU - Hickey, Anthony J. AU - Smith, Hugh D. C. PY - 2010 SN - 1441978550 9786613080585 1441978569 1283080583 PB - New York : Springer, DB - UniCat KW - Pharmacy. KW - Epidemiologic Study Characteristics as Topic KW - Drug Discovery KW - Evaluation Studies as Topic KW - Physiological Phenomena KW - Chemistry, Pharmaceutical KW - Health Care Evaluation Mechanisms KW - Epidemiologic Methods KW - Investigative Techniques KW - Phenomena and Processes KW - Pharmacology KW - Analytical, Diagnostic and Therapeutic Techniques and Equipment KW - Chemistry KW - Quality of Health Care KW - Public Health KW - Environment and Public Health KW - Health Care Quality, Access, and Evaluation KW - Natural Science Disciplines KW - Biological Science Disciplines KW - Health Care KW - Disciplines and Occupations KW - Clinical Trials as Topic KW - Drug Design KW - Pharmacological Phenomena KW - Health & Biological Sciences KW - Pharmacy, Therapeutics, & Pharmacology KW - Drug development. KW - Pharmacology. KW - Drug effects KW - Medical pharmacology KW - Development of drugs KW - Drugs KW - New drug development KW - Development KW - Medicine. KW - Biotechnology. KW - Biochemistry. KW - Biomedicine. KW - Pharmacology/Toxicology. KW - Biochemistry, general. KW - Medical sciences KW - Chemicals KW - Chemotherapy KW - Pharmacy KW - Physiological effect KW - Toxicology. KW - Biological chemistry KW - Chemical composition of organisms KW - Organisms KW - Physiological chemistry KW - Biology KW - Chemical engineering KW - Genetic engineering KW - Medicine KW - Poisoning KW - Poisons KW - Composition KW - Toxicology UR - https://www.unicat.be/uniCat?func=search&query=sysid:14305905 AB - The historical approach to the interpretation of physical, chemical and biological phenomena has been to consider relationships with causative factors that can be reduced to linearity allowing simple and direct interpretation. However, it is increasingly evident that there is often more information in the data than linear interpretations allow. The current capacity for computers to assist in identifying non-linear relationships allows greater interpretation of data which illuminates the phenomena allowing the information to be translated into knowledge that can be used wisely to promote various desirable pharmaceutical outcomes. This short volume is intended to stimulate the reader to contemplate research and development areas in which the data might be more accurately interpreted to allow greater understanding and ultimately control of the pharmaceutically complex phenomena. ER -