I attended and contributed to the recent annual meeting of the American Society for Clinical Pharmacology and Therapeutics (ASCPT) in New Orleans. This is a meeting that I have attended regularly in the past. It was a valuable opportunity to see some truly innovative scientific approaches to the toughest challenges in drug development. If I were to summarize what was remarkable this year, it would be the “Rise of QSP and PBPK.” While present in previous years, quantitative systems pharmacology (QSP) and its sub-branch, physiologically-based pharmacokinetics (PBPK), were thrust into the limelight this year.
As Certara’s CSO, I was glad to see several contributions by our own science team (podium presentations as well as posters). Even more importantly, I noted tens of presentations from our pharmaceutical colleagues, who are applying our methodologies and tools to help with their drug development projects. In this blog post, I’ll discuss five posters highlighting our latest research on PK/PD modeling and simulation (M&S) and PBPK M&S presented by my colleagues at the meeting.
Poster #1: A model relating overall survival related to tumor growth inhibition in renal cell carcinoma patients treated with sunitinib, axitinib or temsirolimus
Authors: Laurent Claret, Brett Houk, François Mercier, Peter A Milligan, René Bruno
Summary: Tumor growth inhibition (TGI) metrics estimated with TGI models have been shown to be predictive of overall survival (OS) in a variety of tumor types. The objectives of this work were to leverage historical data and assess the link between TGI and OS and to identify TGI thresholds that are predictive of expected OS benefit and could be used as targets to support early decisions at end of Phase 2, or at an interim point of a Phase 3 clinical trial.
Poster #2: Integrated pharmacogenomic analysis reveals OATP1B1 T521C polymorphism (rs4149056) does not affect the pharmacokinetics of edoxaban
Authors: Alexander G. Vandell, James Lee, Minggao Shi, Igor Rubets, Karen S. Brown, Joseph R. Walker
Summary: Edoxaban is a once-daily, selective, orally administered direct factor Xa inhibitor approved in the US for reducing the risk of stroke and systemic embolism in patients with non-valvular atrial fibrillation, and for the treatment of venous thromboembolism. It undergoes minimal metabolism, yielding the major metabolite M4, which accounts for <10% of edoxaban exposure. M4 and edoxaban have similar anticoagulant potency.
The organic anion transporter protein 1B1 (OATP1B1), encoded by the SLCO1B1 gene, mediates the hepatic uptake of M4. The T521C single nucleotide polymorphism (rs4149056) of the SLCO1B1 gene is associated with decreased transporter activity of OATP1B1. Individuals carrying this polymorphism may have increased exposure to certain drugs that are OATP1B1 substrates. Pharmacological inhibition of OATP1B1 may contribute to increased M4 exposure. The objective of this analysis was to investigate the association between the SLCO1B1 genotype and the pharmacokinetics (PK) of edoxaban and M4 in healthy subjects who had participated in an edoxaban Phase 1 study.
Poster #3: Application of PBPK and Bayesian modeling for prediction of the likelihood of individual patients experiencing serious adverse reactions to a standard dose of efavirenz
Authors: Manoranjenni Chetty, Theresa Cain, Masoud Jamei, Amin Rostami
Summary: Efavirenz is a non-nucleoside reverse transcriptase inhibitor (NNRTI) used as part of highly active antiretroviral therapy (HAART) for the treatment of a human immunodeficiency virus (HIV) type 1. It is primarily metabolized by CY2B6. A standard 600mg dose of efavirenz has been associated with serious adverse reactions in poor metabolizers (PMs) of CYP2B6, necessitating a reduction in dose.
The objective of this study was to determine whether a single plasma concentration can be useful in identifying PMs when genotyping is unavailable. A physiologically-based pharmacokinetic (PBPK) model, based on the models published by Xu et al, and Siccardi et al, was used to simulate the pharmacokinetics of 600mg single and multiple doses of efavirenz in extensive metabolizers (EMs), intermediate metabolizers (IMs) and PMs of CYP2B6. The models were implemented using the Simcyp simulator and verified using clinical data.
Poster #4: Simulating cardiac consequences of genetic variability at the metabolism level with use of a middle-out approach and flecainide as an example compound
Author: Sebastian Polak
Summary:Recent results from . The aim of this study was to assess whether modeling and simulation (M&S) can be used to predict cardiac consequences of an example drug using a middle-out approach that leverages early clinical trial PK data and in vitro data describing drug-triggered cardiac ionic currents inhibition.
Poster #5: Application of physiologically-based pharmacokinetic (PBPK) modeling for prediction of the exposure of buprenorphine in neonates: Incorporation of CYP3A4 and UGT1A1 ontogenies
Authors: Karen Rowland Yeo, Trevor Johnson, Maurice Dickins, Amin Rostami-Hodjegan
Summary: The prevalence of opioid abuse or dependence during pregnancy increased by 127% from 1998 to 2011. Newborn babies exposed to opioids in utero may experience varying degrees of withdrawal after delivery—neonatal abstinence syndrome (NAS). The features of NAS include low birth weight, poor feeding, and respiratory problems.The partial μ-opioid receptor agonist, buprenorphine, is recommended for infants requiring treatment for NAS.
Buprenorphine is metabolized extensively by CYP3A4 and UGT1A1 and undergoes biliary clearance (CL). Data on developmental physiology and CYP3A4 and UGT1A1 ontogenies were previously available.These were incorporated into a PBPK model and various maturation functions for biliary CL were investigated with the purpose of recovering observed data in neonates under the so-called “middle-out” modeling framework. The findings of this study indicate that the ontogeny of biliary elimination appears to be rapid and may even reach adult levels at birth. More research is required in this area particularly on the ontogeny of specific canalicular transporters in humans.
As you can see, we’re performing an exciting and broad range of work at Certara. By using model based approaches, we are accelerating the pace of drug development while making drugs safer and more effective for ALL patients.
Did you enjoy checking out these posters? If so, I’d also recommend reading our white paper about how PBPK modeling can support drug development decisions, regulatory interactions, and drug labeling.