4 research outputs found

    Preclinical Pharmacokinetic/Pharmacodynamic Modeling and Simulation in the Pharmaceutical Industry: An IQ Consortium Survey Examining the Current Landscape

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    The application of modeling and simulation techniques is increasingly common in preclinical stages of the drug discovery and development process. A survey focusing on preclinical pharmacokinetic/pharmacodynamics (PK/PD) analysis was conducted across pharmaceutical companies that are members of the International Consortium for Quality and Innovation in Pharmaceutical Development. Based on survey responses, ~68% of companies use preclinical PK/PD analysis in all therapeutic areas indicating its broad application. An important goal of preclinical PK/PD analysis in all pharmaceutical companies is for the selection/optimization of doses and/or dose regimens, including prediction of human efficacious doses. Oncology was the therapeutic area with the most PK/PD analysis support and where it showed the most impact. Consistent use of more complex systems pharmacology models and hybrid physiologically based pharmacokinetic models with PK/PD components was less common compared to traditional PK/PD models. Preclinical PK/PD analysis is increasingly being included in regulatory submissions with ~73% of companies including these data to some degree. Most companies (~86%) have seen impact of preclinical PK/PD analyses in drug development. Finally, ~59% of pharmaceutical companies have plans to expand their PK/PD modeling groups over the next 2 years indicating continued growth. The growth of preclinical PK/PD modeling groups in pharmaceutical industry is necessary to establish required resources and skills to further expand use of preclinical PK/PD modeling in a meaningful and impactful manner

    Monoclonal antibody exposure in rat and cynomolgus monkey cerebrospinal fluid following systemic administration

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    Abstract Background Many studies have focused on the challenges of small molecule uptake across the blood–brain barrier, whereas few in-depth studies have assessed the challenges with the uptake of antibodies into the central nervous system (CNS). In drug development, cerebrospinal fluid (CSF) sampling is routinely used as a surrogate for assessing CNS drug exposure and biomarker levels. In this report, we have studied the kinetic correlation between CSF and serum drug concentration–time profiles for five humanized monoclonal antibodies in rats and cynomolgus monkeys and analyzed factors that affect their CSF exposure. Results Upon intravenous (IV) bolus injection, antibodies entered the CNS slowly and reached maximum CSF concentration ( CSF T max ) in one to several days in both rats and monkeys. Antibody serum and CSF concentration–time curves converged until they became parallel after CSF T max was reached. Antibody half-lives in CSF ( CSF t ½ ) approximated their serum half-lives ( serum t ½ ). Although the intended targets of these antibodies were different, the steady-state CSF to serum concentration ratios were similar at 0.1–0.2% in both species. Independent of antibody target and serum concentration, CSF-to-serum concentration ratios for individual monkeys ranged by up to tenfold from 0.03 to 0.3%. Conclusion Upon systemic administration, average antibodies CSF-to-serum concentration ratios in rats and monkeys were 0.1–0.2%. The CSF t ½ of the antibodies was largely determined by their long systemic t ½ ( systemic t ½ )

    Translational pharmacokinetic-pharmacodynamic analysis in the pharmaceutical industry: An IQ Consortium PK-PD Discussion Group perspective

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    With inadequate efficacy being the primary cause for the attrition of drug candidates in clinical development, the need to better predict clinical efficacy earlier in the drug development process has increased in importance in the pharmaceutical industry. Here, we review current applications of translational pharmacokinetic-pharmacodynamic (PK-PD) modeling of preclinical data in the pharmaceutical industry, including best practices. Preclinical translational PK-PD modeling has been used in many therapeutic areas and has been impactful to drug development. The role of preclinical translational PK-PD modeling in drug discovery and development will continue to evolve and broaden, given that its broad implementation in the pharmaceutical industry is relatively recent and many opportunities still exist for its further application
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