Publications by authors named "Karthik Lingineni"

9 Publications

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Physiologically-based pharmacokinetics modeling to investigate formulation factors influencing the generic substitution of dabigatran etexilate.

CPT Pharmacometrics Syst Pharmacol 2021 Mar 10;10(3):199-210. Epub 2021 Feb 10.

Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.

The exposure-response relationship of direct acting oral anti-coagulants (DOACs) for bleeding risk is steep relative to ischemic stroke reduction. As a result, small changes in exposure may lead to bleeding events. The overall goal of this project was to determine the effect of critical formulation parameters on the pharmacokinetics (PKs) and thus safety and efficacy of generic DOACs. In this first installment of our overall finding, we developed and verified a physiologically-based PK (PBPK) model for dabigatran etexilate (DABE) and its metabolites. The model was developed following a middle out approach leveraging available in vitro and in vivo data. External validity of the model was confirmed by overlapping predicted and observed PK profiles for DABE as well as free and total dabigatran for a dataset not used during model development. The verified model was applied to interrogate the impact of modulating the microenvironment pH on DABE systemic exposure. The PBPK exploratory analyses highlighted the high sensitivity of DABE exposure to supersaturation ratio and precipitation kinetics.
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http://dx.doi.org/10.1002/psp4.12589DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965836PMC
March 2021

Quantitative Assessment of Levonorgestrel Binding Partner Interplay and Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling.

CPT Pharmacometrics Syst Pharmacol 2021 01 13;10(1):48-58. Epub 2020 Dec 13.

Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA.

Levonorgestrel (LNG) is the active moiety in many hormonal contraceptive formulations. It is typically coformulated with ethinyl estradiol (EE) to decrease intermenstrual bleeding. Due to its widespread use and CYP3A4-mediated metabolism, there is concern regarding drug-drug interactions (DDIs), particularly a suboptimal LNG exposure when co-administered with CYP3A4 inducers, potentially leading to unintended pregnancies. The goal of this analysis was to determine the impact of DDIs on the systemic exposure of LNG. To this end, we developed and verified a physiologically-based pharmacokinetic (PBPK) model for LNG in PK-Sim (version 8.0) accounting for the impact of EE and body mass index (BMI) on LNG's binding to sex-hormone binding globulin. Model parameters were optimized following intravenous and oral administration of 0.09 mg LNG. The combined LNG-EE PBPK model was verified regarding CYP3A4-mediated interaction by comparing to published clinical DDI study data with carbamazepine, rifampicin, and efavirenz (CYP3A4 inducers). Once verified, the model was applied to predict systemic LNG exposure in normal BMI and obese women (BMI ≥ 30 kg/m ) with and without co-administration of itraconazole (competitive CYP3A4 inhibitor) and clarithromycin (mechanism-based CYP3A4 inhibitor). Total and free LNG exposures, when co-administered with EE, decreased 2-fold in the presence of rifampin, whereas they increased 1.5-fold in the presence of itraconazole. Although changes in total and unbound exposure were decreased in obese women compared with normal BMI women, the relative impact of DDIs on LNG exposure was similar between both groups.
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http://dx.doi.org/10.1002/psp4.12572DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7825189PMC
January 2021

Quantitative Benefit-Risk Assessment of P-gp-Mediated Drug-Drug Interactions of Dabigatran Coadministered With Pharmacokinetic Enhancers in Patients With Renal Impairment.

Clin Pharmacol Ther 2021 01 10;109(1):193-200. Epub 2020 Dec 10.

Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.

Drug-drug interactions (DDIs) between dabigatran and ritonavir/cobicistat are of major concern in people living with HIV, particularly in those with impaired renal function, because they can result in increased dabigatran exposure and thus an increased risk of major bleeding events. However, the extent of this interaction and subsequent need for dose adjustment in subjects with varying degrees of renal function is currently not yet fully understood. To close this knowledge gap, we conducted an integrated population physiologically-based pharmacokinetic/pharmacodynamic analysis linking changes in dabigatran exposure due to DDIs and varying degrees of renal function to the probability of experiencing an ischemic stroke or major bleeding event within 1 year. The results of our analysis suggest that coadministration of dabigatran etexilate (dabigatran prodrug) and ritonavir/cobicistat should be avoided in subjects with severe renal impairment. A 2-hour dose separation or dabigatran etexilate dose reduction to 110 mg b.i.d. (twice daily) should be considered in subjects with moderate renal impairment when coadministered with ritonavir, while the dabigatran etexilate dose should be further reduced to 75 mg b.i.d. when coadministered with cobicistat. No dabigatran etexilate dose adjustment is needed in subjects with normal renal function receiving ritonavir, but dabigatran etexilate dose reduction to 110 mg b.i.d. should be considered when coadministered with cobicistat.
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http://dx.doi.org/10.1002/cpt.2087DOI Listing
January 2021

Examination of Metoprolol Pharmacokinetics and Pharmacodynamics Across CYP2D6 Genotype-Derived Activity Scores.

CPT Pharmacometrics Syst Pharmacol 2020 12 3;9(12):678-685. Epub 2020 Nov 3.

Department of Pharmacotherapy and Translation Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA.

Recent CYP2D6 phenotype standardization efforts by CYP2D6 activity score (AS) are based on limited pharmacokinetic (PK) and pharmacodynamic (PD) data. Using data from two independent clinical trials of metoprolol, we compared metoprolol PK and PD across CYP2D6 AS with the goal of determining whether the PK and PD data support the new phenotype classification. S-metoprolol apparent oral clearance (CLo), adjusted for clinical factors, was correlated with CYP2D6 AS (P < 0.001). The natural log of CLo was lower with an AS of 1 (7.6 ± 0.4 mL/minute) vs. 2-2.25 (8.3 ± 0.6 mL/minute; P = 0.012), similar between an AS of 1 and 1.25-1.5 (7.8 ± 0.5 mL/minute; P = 0.702), and lower with an AS of 1.25-1.5 vs. 2-2.25 (P = 0.03). There was also a greater reduction in heart rate with metoprolol among study participants with AS of 1 (-10.8 ± 5.5) vs. 2-2.25 (-7.1 ± 5.6; P < 0.001) and no significant difference between those with an AS of 1 and 1.25-1.5 (-9.2 ± 4.7; P = 0.095). These data highlight linear trends among CYP2D6 AS and metoprolol PK and PD, but inconsistencies with the phenotypes assigned by AS based on the current standards. Overall, this case study with metoprolol suggests that utilizing CYP2D6 AS, instead of collapsing AS into phenotype categories, may be the most precise approach for utilizing CYP2D6 pharmacogenomics in clinical practice.
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http://dx.doi.org/10.1002/psp4.12563DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762806PMC
December 2020

Development and Verification of a Body Weight-Directed Disease Trial Model for Glucose Homeostasis.

J Clin Pharmacol 2021 02 7;61(2):234-243. Epub 2020 Sep 7.

Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.

Weight loss has been associated with improvement in insulin sensitivity. It is consequently a cornerstone in the management of type 2 diabetes mellitus (T2DM). However, the strictly quantitative relationship between weight loss, insulin sensitivity, and clinically relevant glucose homeostasis biomarkers as well as changes therein as T2DM progresses is not yet fully understood. Therefore, the objective of our research was to establish a body weight-directed disease trial model for glucose homeostasis. To that end, we conducted a model-based meta-analysis using time course data of body weight loss (following lifestyle change or surgical procedure) and corresponding improvement of insulin sensitivity expressed as the Matsuda index. Changes in body weight were best described by a sigmoidal E model, whereas changes in the Matsuda index were best described by a linear model with a slope of 3.49. Once developed and verified, the model-based meta-analysis was linked to a disease-drug trial model for T2DM previously developed by our group to characterize and predict the impact of weight loss on clinically relevant glucose homeostasis biomarkers. The joint model was then used to conduct clinical trial simulations, which showed that weight loss can greatly improve clinically relevant glucose homeostasis biomarkers in T2DM patients.
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http://dx.doi.org/10.1002/jcph.1728DOI Listing
February 2021

Predicting Cost-Effectiveness of Generic vs. Brand Dabigatran Using Pharmacometric Estimates Among Patients with Atrial Fibrillation in the United States.

Clin Transl Sci 2020 03 13;13(2):352-361. Epub 2020 Feb 13.

Department of Pharmaceutical Outcomes and Policy, Center for Drug Evaluation & Safety, University of Florida College of Pharmacy, Gainesville, Florida, USA.

Generic entry of newer anticoagulants is expected to decrease the costs of atrial fibrillation management. However, when making switches between brand and generic medications, bioequivalence concerns are possible. The objectives of this study were to predict and compare the lifetime cost-effectiveness of brand dabigatran with hypothetical future generics. Markov microsimulations were modified to predict the lifetime costs and quality-adjusted life years of patients on either brand or generic dabigatran from a US private payer perspective. Event rates for generics were predicted using previously developed pharmacokinetic-pharmacodynamic models. The analyses showed that generic dabigatran with lower-than-brand systemic exposure were dominant. Meanwhile, generic dabigatran with extremely high systemic exposure was not cost-effective compared with the brand reference. Cost-effectiveness of generic medications cannot always be assumed as shown in this example. Combined use of pharmacometric and pharmacoeconomic models can assist in decision making between brand and generic pharmacotherapies.
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http://dx.doi.org/10.1111/cts.12719DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070788PMC
March 2020

Evaluating the Clinical Impact of Formulation Variability: A Metoprolol Extended-Release Case Study.

J Clin Pharmacol 2019 09 14;59(9):1266-1274. Epub 2019 May 14.

Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL, USA.

The objective of this research was to evaluate the impact of changes in the formulation of metoprolol extended-release (ER) tablets on dissolution, pharmacokinetic, and exercise-induced heart rate (EIHR) using a combined physiologically based absorption pharmacokinetic, and population pharmacokinetic/pharmacodynamic modeling and simulation approach. Using a previously developed physiologically based absorption pharmacokinetic model in DDDPlus and GastroPlus, we simulated the changes in drug release and exposure as the result of quantitative changes in the release-controlling excipient, hydroxylpropylmethylcellulose, for 50 and 200 mg. The similarity of dissolution profiles was assessed using the f test, and bioequivalence was tested on the simulated pharmacokinetic profiles. We used the simulated concentration-time profiles following formulation changes as pharmacokinetic input into a population pharmacokinetic/pharmacodynamic model newly developed in NONMEM to determine if changes in pharmacokinetics lead to clinically significant changes in pharmacodynamics. Pharmacodynamic assessment was based on the percentage reduction in the EIHR from baseline. Therapeutic effect was considered similar when the model-predicted EIHR was within 50% to 85% of the average maximum EIHR of healthy 30-year-old subjects. A 40% or more increase in the release rate constant resulted in dissimilarity in dissolution profiles and bioINequivalence in pharmacokinetics for both 50 and 200 mg. Formulation-related differences in drug release of metoprolol ER tablets can lead to differences in pharmacokinetics. However, the evaluated pharmacokinetic differences do not lead to clinically meaningful differences in EIHR, suggesting that EIHR may not be sensitive enough to detect changes in pharmacokinetics of metoprolol ER products.
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http://dx.doi.org/10.1002/jcph.1433DOI Listing
September 2019

The role of multidrug resistance protein (MRP-1) as an active efflux transporter on blood-brain barrier (BBB) permeability.

Mol Divers 2017 May 3;21(2):355-365. Epub 2017 Jan 3.

Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector-67, S.A.S. Nagar, Punjab, 160062, India.

Drugs acting on central nervous system (CNS) may take longer duration to reach the market as these compounds have a higher attrition rate in clinical trials due to the complexity of the brain, side effects, and poor blood-brain barrier (BBB) permeability compared to non-CNS-acting compounds. The roles of active efflux transporters with BBB are still unclear. The aim of the present work was to develop a predictive model for BBB permeability that includes the MRP-1 transporter, which is considered as an active efflux transporter. A support vector machine model was developed for the classification of MRP-1 substrates and non-substrates, which was validated with an external data set and Y-randomization method. An artificial neural network model has been developed to evaluate the role of MRP-1 on BBB permeation. A total of nine descriptors were selected, which included molecular weight, topological polar surface area, ClogP, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, P-gp, BCRP, and MRP-1 substrate probabilities for model development. We identified 5 molecules that fulfilled all criteria required for passive permeation of BBB, but they all have a low logBB value, which suggested that the molecules were effluxed by the MRP-1 transporter.
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http://dx.doi.org/10.1007/s11030-016-9715-6DOI Listing
May 2017

Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

Comb Chem High Throughput Screen 2015 ;18(5):476-85

Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector-67, S.A.S. Nagar, Mohali, Punjab-160062, India.

The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this work, a computational model was developed to predict the compounds as BCRP inhibitors or non-inhibitors. Various machine learning approaches like, support vector machine (SVM), k-nearest neighbor (k-NN) and artificial neural network (ANN) were used to develop the models. The Matthews correlation coefficients (MCC) of developed models using ANN, k-NN and SVM are 0.67, 0.71 and 0.77, and prediction accuracies are 85.2%, 88.3% and 90.8% respectively. The developed models were tested with a test set of 99 compounds and further validated with external set of 98 compounds. Distribution plot analysis and various machine learning models were also developed based on druglikeness descriptors. Applicability domain is used to check the prediction reliability of the new molecules.
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http://dx.doi.org/10.2174/1386207318666150525094503DOI Listing
February 2016