Clinical pharmacology and therapeutics
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Adaptive Biomedical Innovation (ABI) is a multistakeholder approach to product and process innovation aimed at accelerating the delivery of clinical value to patients and society. ABI offers the opportunity to transcend the fragmentation and linearity of decision-making in our current model and create a common collaborative framework that optimizes the benefit and access of new medicines for patients as well as creating a more sustainable innovation ecosystem.
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Clin. Pharmacol. Ther. · Dec 2016
Adaptive Biomedical Innovation: Evolving Our Global System to Sustainably and Safely Bring New Medicines to Patients in Need.
The current system of biomedical innovation is unable to keep pace with scientific advancements. We propose to address this gap by reengineering innovation processes to accelerate reliable delivery of products that address unmet medical needs. ⋯ ABI involves bringing stakeholders together to set shared objectives, foster trust, structure decision-making, and manage expectations through rapid-cycle feedback loops that maximize product knowledge and reduce uncertainty in a continuous, adaptive, and sustainable learning healthcare system. Adaptive decision-making, a core element of ABI, provides a framework for structuring decision-making designed to manage two types of uncertainty - the maturity of scientific and clinical knowledge, and the behaviors of other critical stakeholders.
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Clin. Pharmacol. Ther. · Dec 2016
The Impact of Breakthrough Therapy Designation on Development Strategies and Timelines for Nononcology Drugs and Vaccines.
The US Food and Drug Administration (FDA) Safety and Innovation Act (FDASIA, 2012) introduced the Breakthrough Therapy Designation (BTD), a new tool to expedite development of medicines to treat serious or life-threatening diseases. The majority of BTDs have gone to oncology drugs, and a recent publication by Shea et al.1 reviewed the impact of BTD on oncology drug development. This article reviews the impact of BTD on development strategies and timelines for nononcology drugs.
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Clin. Pharmacol. Ther. · Dec 2016
Bottom-up Meets Top-down: Complementary Physiologically Based Pharmacokinetic and Population Pharmacokinetic Modeling for Regulatory Approval of a Dosing Algorithm of Valganciclovir in Very Young Children.
Population pharmacokinetic (PopPK) and physiologically based pharmacokinetic (PBPK) models are frequently used to support pediatric drug development. Both methods have strengths and limitations and we used them complementarily to support the regulatory approval of a dosing algorithm for valganciclovir (VGCV) in children <4 months old. ⋯ PBPK and PopPK confirmed that the proposed VGCV dosing algorithm achieves similar GCV exposures in children of all ages and that the alternative dosing algorithm leads to underexposure in a substantial fraction of patients. Our approach raised the confidence in the VGCV dosing algorithm for children <4 months old and supported the regulatory approval.
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Clin. Pharmacol. Ther. · Sep 2016
Implications of Programmed Cell Death 1 Ligand 1 Heterogeneity in the Selection of Patients With Non-Small Cell Lung Cancer to Receive Immunotherapy.
The use of programmed cell death 1 ligand 1 (PD-L1) as a predictive biomarker to select patients to receive programmed cell death 1 (PD-1) or PD-L1 inhibitors in non-small cell lung cancer (NSCLC) is limited by the definitions of positivity, interassay agreement, and intra- and intertumoral heterogeneity of expression. Although PD-L1 expression enriches for responses, the lack of expression does not exclude clinical benefit.