Predicting Pharmacokinetics/Pharmacodynamics in the Individual Patient: Separating Reality From Hype

Computational prediction of toxicity of small organic molecules: state-of-the-art

The field of computational prediction of various toxicity end-points has evolved over last two decades significantly. Availability of newer modelling techniques, powerful computational resources and good-quality data have made it possible to generate reliable predictions for new chemical entities, impurities, chemicals, natural products and a lot of other substances. The field is still undergoing metamorphosis to take into account molecular complexities underlying toxicity end-points such as teratogenicity, mutagenicity, carcinogenicity, etc. Expansion of the applicability domain of these predictive models into areas other than life sciences, such as environmental and materials sciences have received a great deal of attention from all walks of life, fuelling further development and growth of the field. The present chapter discusses the state-of-the-art computational prediction of toxicity end-points of small organic molecules to balance the trade-off between the molecular complexity and the quality of such predictions, without compromising their immense utility in many fields.

Preclinical Assessment of Cardiac Valve Substitutes: Current Status and Considerations for Engineered Tissue Heart Valves

Tissue engineered heart valve (TEHV) technology may overcome deficiencies of existing available heart valve substitutes. The pathway by which TEHVs will undergo development and regulatory approval has several challenges. In this communication, we review: (1) the regulatory framework for regulation of medical devices in general and substitute heart valves in particular; (2) the special challenges of preclinical testing using animal models for TEHV, emphasizing the International Standards Organization (ISO) guidelines in document 5840; and (3) considerations that suggest a translational roadmap to move TEHV forward from pre-clinical to clinical studies and clinical implementation.

Pharmacogenomics/updated for precision medicine in dermatology

Pharmacogenomics, a key part of precision medicine, has the potential to tailor drug therapy with the high safety margins and optimized response. Before the Human Genome Project in 2003, articles on pharmacogenomics were limited. The last 15 years have seen significant growth in the field, with gene variant discoveries that play essential roles in individuals' drug response. Dermatology has started to take advantage of this information. This overview shows how pharmacogenomic databases have expanded in the treatment of skin diseases and provides a list of current dermatologic drugs with their FDA-approved biomarkers and clinical implementation.

Why Drugs Fail in Late Stages of Development: Case Study Analyses from the Last Decade and Recommendations

New drug development is both resource and time intensive, where later clinical stages result in significant costs. We analyze recent late-stage failures to identify drugs where failures result from inadequate scientific advances as well as drugs where we believe pitfalls could have been avoided. These can be broadly classified into two categories: 1) where science is mature and the failures can be avoided through rigorous and prospectively determined decision-making criteria, scientific curiosity, and discipline to follow up on emerging findings; and 2) where problems encountered in Phase 3 failures cannot be explained at this time, as the science is not sufficiently advanced and companies/investigators need to recognize the possibility of deficiency of our knowledge. Through these case studies, key themes critical for successful drug development emerge-understanding the therapeutic pathway including receptor and signaling biology, pharmacological responses related to safety and efficacy, pharmacokinetics of the drug and exposure at target site, optimum dose, and dosing regimen; and identification of patient sub-populations likely to respond and will have a favorable benefit-risk profile, design of clinical trials, and a quantitative framework that can guide data-driven decision making. It is essential that the right studies are conducted early in the development process to answer the key questions, with the emphasis on learning in the early stages of development, whereas Phase 3 should be reserved for confirming the safety and efficacy. Utilization of innovative technology in identifying patients based on molecular signature of their disease, rapid assessment of pharmacological response, mechanistic modeling of emerging data, seamless operational processes to reduce start-up and wind-down time for clinical trials through use of electronic health records and data mining, and development of novel and objective clinical efficacy endpoints are some concepts for improving the success rate.