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1. Covariate modeling in pharmacometrics: General points for consideration

Author

Kinjal Sanghavi, Jakob Ribbing, James A. Rogers, Mariam A. Ahmed, Mats O. Karlsson, Nick Holford, Estelle Chasseloup, Malidi Ahamadi, Kenneth G. Kowalski, Susan Cole, Essam Kerwash, Janet R. Wade, Chao Liu, Yaning Wang, Mirjam N. Trame, Hao Zhu, Justin J. Wilkins, and for the ISoP Standards & Best Practices Committee

Subjects
Therapeutics. Pharmacology, RM1-950
Abstract

Abstract Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or the planning of clinical studies in different population subgroups. The pharmacometric literature has amassed a diverse, complex, and evolving collection of methodologies and interpretive guidance related to covariate modeling. With the number and complexity of technologies increasing, a need for an overview of the state of the art has emerged. In this article the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee presents perspectives on best practices for planning, executing, reporting, and interpreting covariate analyses to guide pharmacometrics decision making in academic, industry, and regulatory settings.

Published
2024
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2. Evaluation of the effect of erenumab on migraine‐specific questionnaire in patients with chronic and episodic migraine

Author

Po‐Wei Chen, Mats O. Karlsson, Sebastian Ueckert, Ari Pritchard‐Bell, Cheng‐Pang Hsu, Sandeep Dutta, and Malidi Ahamadi

Subjects
Therapeutics. Pharmacology, RM1-950
Abstract

Abstract Erenumab is a fully human anti‐canonical calcitonin gene‐related peptide receptor monoclonal antibody approved for migraine prevention. The Migraine‐Specific Quality‐of‐Life Questionnaire (MSQ) is a 14‐item patient‐reported outcome instrument that measures the impact of migraine on health‐related quality of life. Erenumab data from four phase II/III clinical trials were used to develop an item response theory (IRT) model within a nonlinear mixed effects framework, (i) evaluate the MSQ item information with respect to patient disability, (ii) characterize the longitudinal progression of the MSQ, and (iii) quantify the effect of erenumab on the MSQ in patients with migraine. The majority (80%) of information was found to be contained in 9 out of 14 items, extending the current knowledge on the reliability of the MSQ as a psychometric tool. Simulations across three MSQ domains show significant improvement from baseline, exceeding minimally important differences. Overall, the IRT model platform developed herein allows for systematic quantification of the effect of erenumab on the MSQ in patients with migraine.

Published
2023
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3. Oncolytic viral kinetics mechanistic modeling of Talimogene Laherparepvec (T‐VEC) a first‐in‐class oncolytic viral therapy in patients with advanced melanoma

Author

Malidi Ahamadi, Johannes Kast, Po‐Wei Chen, Xiaojun Huang, Sandeep Dutta, and Vijay V. Upreti

Subjects
Therapeutics. Pharmacology, RM1-950
Abstract

Abstract Talimogene Laherparepvec (T‐VEC) is a first‐in‐class oncolytic virotherapy approved for the treatment of unresectable melanoma recurrent after initial surgery. Biodistribution data from a phase II study was used to develop a viral kinetic mechanistic model describing the interaction between cytokines such as granulocyte‐macrophage colony‐stimulating factor (GM‐CSF), the immune system, and T‐VEC treatment. Our analysis found that (1) the viral infection rate has a great influence on T‐VEC treatment efficacy; (2) an increase in T‐VEC dose of 102 plaque‐forming units/ml 21 days and beyond after the initial dose of T‐VEC resulted in an ~12% increase in response; and (3) at the systemic level, the ratio of resting innate immune cells to the death rate of innate immune impact T‐VEC treatment efficacy. This analysis clarifies under which condition the immune system either assists in eliminating tumor cells or inhibits T‐VEC treatment efficacy, which is critical to both efficiently design future oncolytic agents and understand cancer development.

Published
2023
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4. Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T‐cellular therapy development

Author

Johannes Kast, Saeideh Nozohouri, Di Zhou, Marc R. Yago, Po‐Wei Chen, Malidi Ahamadi, Sandeep Dutta, and Vijay V. Upreti

Subjects
Therapeutics. Pharmacology, RM1-950, Public aspects of medicine, RA1-1270
Abstract

Abstract Advances in immuno‐oncology have provided a variety of novel therapeutics that harness the innate immune system to identify and destroy neoplastic cells. It is noteworthy that acceptable safety profiles accompany the development of these targeted therapies, which result in efficacious cancer treatment with higher survival rates and lower toxicities. Adoptive cellular therapy (ACT) has shown promising results in inducing sustainable remissions in patients suffering from refractory diseases. Two main types of ACT include engineered Chimeric Antigen Receptor (CAR) T cells and T cell receptor (TCR) T cells. The application of these immuno‐therapies in the last few years has been successful and has demonstrated a safe and rapid treatment regimen for solid and non‐solid tumors. The current review presents an insight into the clinical pharmacology aspects of immuno‐therapies, especially CAR‐T cells. Here, we summarize the current knowledge of TCR and CAR‐T cell immunotherapy with particular focus on the structure of CAR‐T cells, the effects and toxicities associated with these therapies in clinical trials, risk mitigation strategies, dose selection approaches, and cellular kinetics. Finally, the quantitative approaches and modeling techniques used in the development of CAR‐T cell therapies are described.

Published
2022
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5. Molecular Neuroimaging of the Dopamine Transporter as a Patient Enrichment Biomarker for Clinical Trials for Early Parkinson's Disease

Author

Klaus Romero, Daniela Conrado, Jackson Burton, Timothy Nicholas, Vikram Sinha, Sreeraj Macha, Malidi Ahamadi, Jesse Cedarbaum, John Seibyl, Kenneth Marek, Peter Basseches, Derek Hill, Ed Somer, Jill Gallagher, David T. Dexter, Arthur Roach, Diane Stephenson, for the Critical Path for Parkinson's (CPP) Consortium, and the Parkinson's Progression Markers Initiative (PPMI)

Subjects
Therapeutics. Pharmacology, RM1-950, Public aspects of medicine, RA1-1270
Abstract

The Critical Path for Parkinson's (CPP) Imaging Biomarker and Modeling and Simulation working groups aimed to achieve qualification opinion by the European Medicines Agency (EMA) Committee for Medical Products for Human Use (CHMP) for the use of baseline dopamine transporter neuroimaging for patient selection in early Parkinson's disease clinical trials. This paper describes the regulatory science strategy to achieve this goal. CPP is an international consortium of three Parkinson's charities and nine pharmaceutical partners, coordinated by the Critical Path Institute.

Published
2019
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6. Evaluation of dosing strategy for pembrolizumab for oncology indications

Author

Tomoko Freshwater, Anna Kondic, Malidi Ahamadi, Claire H. Li, Rik de Greef, Dinesh de Alwis, and Julie A. Stone

Subjects
Pembrolizumab, Fixed dose, Flat dose, Dosing strategy, Clinical dose, Exposure-response analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Traditionally, most monoclonal antibodies (mAbs) have been dosed based on body weight because of perceived contribution of body size in pharmacokinetic variability. The same approach was used in the initial pembrolizumab studies; however, following availability of PK data, the need for weight-based dosing for pembrolizumab was reassessed. Methods A previously established population PK (popPK) model as well as exposure-response results from patients with advanced melanoma or non–small cell lung cancer (NSCLC) were used to evaluate the potential application of a fixed dosing regimen with the aim of maintaining pembrolizumab exposures within the range demonstrated to provide near maximal efficacy and acceptable safety. Individual PK exposures for the selected fixed dosing regimen from recently completed trials with head and neck cancer, NSCLC, microsatellite instability high (MSI-H) in colorectal cancer (CRC) and urothelial cancer were used to confirm acceptability. To determine whether fixed dosing would maintain exposures within the range of clinical experience, the individual AUC distributions with fixed dosing were compared with the range of exposures from the pembrolizumab doses that were evaluated in early studies (2 mg/kg Q3W, 10 mg/kg Q3W/Q2W). Results Body-weight dependence of clearance was characterized by a power relationship with an exponent of 0.578, a value consistent with fixed- and weight-based dosing providing similar control of PK variability. A fixed dose of 200 mg Q3W was investigated in trials based on predicted exposures maintained within the established exposure range in all patients. Mean (% CV, n) AUCss, 6-weeks was 1.87 (37%, 830), 1.38 (38%, 760) and 7.63 (35%, 1405) mg*day/mL in patients receiving 200 mg, 2 mg/kg and 10 mg/kg Q3W pembrolizumab. High-weight patients had the lowest exposures with 200 mg Q3W; however, exposures in this group (>90 kg) were within the range of prior clinical experience at 2 mg/kg Q3W associated with near maximal efficacy. Conclusions Doses of 200 mg and 2 mg/kg provide similar exposure distributions with no advantage to either dosing approach with respect to controlling PK variability. These findings suggest that weight-based and fixed-dose regimens are appropriate for pembrolizumab.

Published
2017
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7. Oncolytic Viral Kinetics Mechanistic Modeling of Talimogene Laherparepvec (IMLYGIC®) a First-in-Class Oncolytic Viral Therapy in patients with Advanced Melanoma

Author

Malidi Ahamadi, Johannes Kast, Po‐Wei Chen, Xiaojun Huang, Sandeep Dutta, and Vijay V. Upreti

Subjects
Modeling and Simulation, Pharmacology (medical)
Abstract

Talimogene Laherparepvec (T-VEC) is a first in class oncolytic virotherapy approved for the treatment of unresectable melanoma recurrent after initial surgery. Biodistribution data from phase 2 study was used to develop a viral kinetics mechanistic model describing the interaction between cytokines like granulocyte-macrophage colony-stimulating factor (GM-CSF), immune system and T-VEC treatment. Our analysis found 1) viral infection rate has great influence on T-VEC treatment efficacy, 2) an increase of T-VEC dose of 10

Published
2022

9. Development of a Disease Progression Model for Leucine‐Rich Repeat Kinase 2 in Parkinson's Disease to Inform Clinical Trial Designs

Author

Romeo Maciuca, Rachael A Lawson, Timothy Nicholas, David T. Dexter, Malidi Ahamadi, Chao Chen, David J. Burn, Kenneth Marek, Minhua Yang, Klaus Romero, Bob Stafford, Sreeraj Macha, Julie A. Stone, Diane Stephenson, Jackson Burton, Daniela J. Conrado, Vikram Sinha, Hans Smit, Massimo Bani, Mussie Akalu, Jill Gallagher, Babak Boroojerdi, Jonas Weidemann, and Charles S. Venuto

Subjects
Adult, Male, Research design, Oncology, medicine.medical_specialty, Parkinson's disease, Disease, Leucine-Rich Repeat Serine-Threonine Protein Kinase-2, 030226 pharmacology & pharmacy, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Humans, Medicine, Pharmacology (medical), Aged, Aged, 80 and over, Pharmacology, Clinical Trials as Topic, business.industry, Incidence (epidemiology), Parkinson Disease, Middle Aged, Models, Theoretical, medicine.disease, LRRK2, Clinical trial, Research Design, 030220 oncology & carcinogenesis, Concomitant, Mutation, Disease Progression, Female, business, Cohort study
Abstract

A quantitative assessment of Parkinson’s disease (PD) progression is critical for optimizing clinical trials design. Disease progression model was developed using pooled data from the Progression Marker Initiative study and the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation in Parkinson’s Disease study. Age, gender, concomitant medication, and study arms were predictors of baseline. A mutation in the leucine-rich repeat kinase 2 (LRRK2) encoding gene was associated with the disease progression rate. The progression rate in subjects with PD who carried LRRK2 mutation was slightly slower (~0.170 points/month) than that in PD subjects without the mutation (~0.222 points/month). For a non-enriched placebo-controlled clinical trial, approximately 70 subjects/arm would be required to detect a drug effect of 50% reduction in the progression rate with 80% probability. Whereas, 85, 93 and 100 subjects/arm would be required for an enriched clinical trial with 30%, 50% and 70% subjects with LRRK2 mutations, respectively.

Published
2019
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10. Population Pharmacokinetic Properties of Omecamtiv Mecarbil in Healthy Subjects and Patients With Heart Failure With Reduced Ejection Fraction

Author

Po-Wei Chen, Ashit Trivedi, Edward Lee, Sandeep Dutta, and Malidi Ahamadi

Subjects
Pharmacology, Heart Failure, Humans, Urea, Stroke Volume, Cardiology and Cardiovascular Medicine, Healthy Volunteers
Abstract

Omecamtiv mecarbil is a small molecule that has been shown to improve cardiac function in patients with heart failure (HF) with reduced ejection fraction and is currently being developed as an oral modified release tablet for subjects with chronic HF. The objectives of this study were to analyze the pharmacokinetic (PK) properties of omecamtiv mecarbil and to investigate the effects of potential covariates on pertinent PK parameters using population PK modeling of data from 3 clinical trials in healthy subjects (n = 85) and 3 clinical trials in patients with HF (n = 4261). The population PK analysis was performed using a nonlinear mixed effects modeling approach. Omecamtiv mecarbil has a clearance of 11.7 L/h (0.701% relative standard error) and a central volume distribution of 275 L (2.12% relative standard error). The estimated half-life of omecamtiv mecarbil was 33 hours. Body weight and estimated glomerular filtration rate were significant covariates, but their effect on exposure was modest and lacked clinical relevance. Additional covariates, including sex, race, bilirubin, albumin, concomitant medications, New York Heart Association Functional Classification, N-terminal-pro hormone B-type natriuretic peptide, troponin I, creatine kinase MB, serum hemoglobin, tablet formulation, aspartate aminotransferase, and serum urea, were tested and found to have no impact on omecamtiv mecarbil exposures. The results of this integrated evaluation of the impact of covariates on the systemic exposure of omecamtiv mecarbil suggest that dose adjustment is not required for the studied subpopulations of patients with HF.

Published
2021

11. Operating characteristics of stepwise covariate selection in pharmacometric modeling

Author

Anna Largajolli, Malidi Ahamadi, Akshita Chawla, Thomas Kerbusch, Ferdous Gheyas, Rik de Greef, Paul M. Diderichsen, Han Witjes, and Casey B. Davis

Subjects
Pharmacology, Models, Statistical, Model selection, Collinearity, Covariance, Models, Biological, 030226 pharmacology & pharmacy, NONMEM, 03 medical and health sciences, 0302 clinical medicine, Sample size determination, Sample Size, 030220 oncology & carcinogenesis, Stochastic simulation, Statistics, Covariate, Humans, Computer Simulation, Algorithms, Selection (genetic algorithm), Mathematics
Abstract

Stepwise covariate modeling (SCM) is a widely used tool in pharmacometric analyses to identify covariates that explain between-subject variability (BSV) in exposure and exposure–response relationships. However, this approach has several potential weaknesses, including over-estimated covariate effect and incorrect selection of covariates due to collinearity. In this work, we investigated the operating characteristics (i.e., accuracy, precision, and power) of SCM in a controlled setting by simulating sixteen scenarios with up to four covariate relationships. The SCM analysis showed a decrease in the power to detect the true covariates as model complexity increased. Furthermore, false highly correlated covariates were frequently selected in place of or in addition to the true covariates. Relative root mean square errors (RMRSE) ranged from 1 to 51% for the fixed effects parameters, increased with the number of covariates included in the model, and were slightly higher than the RMRSE obtained with a simple re-estimation exercise with the true model (i.e., stochastic simulation and estimation). RMRSE for BSV increased with the number of covariates included in the model, with a covariance parameter RMRSE of almost 135% in the most complex scenario. Loose boundary conditions on the continuous covariate power relation appeared to have an impact on the covariate model selection in SCM. A stricter boundary condition helped achieve high power (> 90%), even in the most complex scenario. Finally, reducing the sample size in terms of number of subjects or number of samples proved to have an impact on the power to detect the correct model.

Published
2019
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12. Performance of longitudinal item response theory models in shortened or partial assessments

Author

Sebastian Ueckert, Sreeraj Macha, Leticia Arrington, Malidi Ahamadi, and Mats O. Karlsson

Subjects
Composite score, Motor Activity, Models, Biological, Severity of Illness Index, 030226 pharmacology & pharmacy, behavioral disciplines and activities, Item response theory, Antiparkinson Agents, 03 medical and health sciences, Pharmaceutical Sciences, 0302 clinical medicine, Pharmacometrics, Statistics, Humans, Computer Simulation, Longitudinal Studies, Drug effect, Mathematics, Pharmacology, Original Paper, Disease progression, Contrast (statistics), Parkinson Disease, Farmaceutiska vetenskaper, Treatment Outcome, Information function, Simulated data, Disease Progression, Item information, Metric (unit), Drug Monitoring, 030217 neurology & neurosurgery
Abstract

This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information content, the assessment was reduced by removal of items in multiple increments and the models’ ability to recover the item characteristics of the remaining items at each level was evaluated. This evaluation was done for both simulated and real data. The metric of comparison in both cases was the item information function. For real data, the impact of shortening on the estimated disease progression and drug effect was also studied. In the simulated data setting, the item characteristics did not differ between the full and the shortened assessments down to the lowest level of information remaining; indicating a considerable independence between items. In contrast when reducing the assessment in a real data setting, a substantial change in item information was observed for some of the items. Disease progression and drug effect estimates also decreased in the reduced assessments. These changes indicate a shift in the measured construct of the shortened assessment and warrant caution when comparing results from a partial assessment with results from the full assessment. Electronic supplementary material The online version of this article (10.1007/s10928-020-09697-x) contains supplementary material, which is available to authorized users.

Published
2020

13. Time dependent pharmacokinetics of pembrolizumab in patients with solid tumor and its correlation with best overall response

Author

Patricia Keegan, Chao Liu, Gideon M. Blumenthal, Malidi Ahamadi, Anna Georgieva Kondic, Manash Shankar Chatterjee, David C. Turner, Jiang Liu, Julie A. Stone, Claire Li, Sriram Subramaniam, Jingyu Yu, Rik de Greef, Atiqur Rahman, Hong Zhao, Brian Booth, Hongshan Li, and Yaning Wang

Subjects
Adult, Male, Oncology, medicine.medical_specialty, Time Factors, Adolescent, medicine.drug_class, medicine.medical_treatment, Antineoplastic Agents, Pembrolizumab, Pharmacology, Antibodies, Monoclonal, Humanized, Monoclonal antibody, 030226 pharmacology & pharmacy, Correlation, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Pharmacokinetics, Carcinoma, Non-Small-Cell Lung, Internal medicine, medicine, Humans, Lung cancer, Melanoma, Aged, Aged, 80 and over, Clinical Trials as Topic, business.industry, Head and neck cancer, Immunotherapy, Middle Aged, medicine.disease, 030220 oncology & carcinogenesis, Female, business
Abstract

Pembrolizumab is a monoclonal antibody that targets the programmed death-1 receptor to induce immune-mediated clearance (CL) of tumor cells. Originally approved by the US Food and Drug Administration in 2014 for treating patients with unresectable or metastatic melanoma, pembrolizumab is now also used to treat patients with non-small-cell lung cancer, classical Hodgkin lymphoma, head and neck cancer, and urothelial cancer. This paper describes the recently identified feature of pembrolizumab pharmacokinetics, the time-dependent or time-varying CL. Overall results indicate that CL decreases over the treatment period of a typical patient in a pattern well described by a sigmoidal function of time with three parameters: the maximum proportion change in CL from baseline (approximately Imax or exactly eImax − 1), the time to reach Imax/2 (TI50), and a Hill coefficient. Best overall response per response evaluation criteria in solid tumor category was found to be associated with the magnitude of Imax.

Published
2017
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14. Challenges in Alzheimer's Disease Drug Discovery and Development: The Role of Modeling, Simulation, and Open Data

Author

Sridhar Duvvuri, Carla Biesdorf, Juan Francisco Morales, Brian Corrigan, Klaus Romero, Diane Stephenson, Sreeraj Macha, Hugo Geerts, Malidi Ahamadi, Gregory Hather, Jackson Burton, Jagdeep T. Podichetty, Timothy Nicholas, Daniela J. Conrado, and Mirjam N. Trame

Subjects
Pharmacology, Clinical Trials as Topic, Drug discovery, Process (engineering), Computer science, Data Collection, Disease, medicine.disease, 030226 pharmacology & pharmacy, Translational Research, Biomedical, 03 medical and health sciences, Open data, 0302 clinical medicine, Drug development, Risk analysis (engineering), Drug Development, Alzheimer Disease, 030220 oncology & carcinogenesis, Drug Discovery, medicine, Dementia, Animals, Humans, Pharmacology (medical), Computer Simulation
Abstract

Alzheimer's disease (AD) is the leading cause of dementia worldwide. With 35 million people over 60 years of age with dementia, there is an urgent need to develop new treatments for AD. To streamline this process, it is imperative to apply insights and learnings from past failures to future drug development programs. In the present work, we focus on how modeling and simulation tools can leverage open data to address drug development challenges in AD.

Published
2019

15. Population pharmacokinetics of orally administrated bromopride: Focus on the absorption process

Author

Gustavo Mendes Lima Santos, Elza Kimura, Marcos Luciano Bruschi, Malidi Ahamadi, Bibiana Verlindo de Araújo, Larissa Lachi-Silva, Aline Bergesch Barth, and Andréa Diniz

Subjects
Adult, Male, medicine.drug_class, Metoclopramide, Pharmaceutical Science, Administration, Oral, Biological Availability, 02 engineering and technology, Absorption (skin), Population pharmacokinetics, Pharmacology, Bioequivalence, 030226 pharmacology & pharmacy, Dosage form, 03 medical and health sciences, 0302 clinical medicine, Pharmacokinetics, Bromopride, medicine, Antiemetic, Humans, Retrospective Studies, Volume of distribution, business.industry, 021001 nanoscience & nanotechnology, Kinetics, Gastrointestinal Absorption, Antiemetics, Female, 0210 nano-technology, business, Brazil, medicine.drug
Abstract

Bromopride is a prokinetic and antiemetic drug used to treat nausea and vomiting. Although its prescription is common in Brazil, there is a lack of studies about bromopride pharmacokinetics. Therefore, the aims of this study were to investigate the population pharmacokinetics of bromopride and to evaluate the influence of covariates on its absorption. This study is a retrospective analysis of data collected from bioequivalence studies. The data was modeled using MONOLIX 2018R2. Assuming one-compartment and linear elimination, the absorption phase was evaluated with different structural models. The model of sequential first- and zero-order with combined error and exponential inter-individual variability in all parameters best described the atypical absorption profile of bromopride. Population estimates were first-order absorption rate (ka) of 0.08 h − 1, fraction of dose absorbed by first-order (Fr) of 32.60%, duration of the zero-order absorption (Tk0) of 0.88 h with latency time (Tlag) of 0.47 h, volume of distribution of 230 l and clearance of 46.80 l h − 1. Bodyweight affects Tk0, dosage form was found to correlate with Tk0 and Tlag, while gender affects Tlag. However, simulations evaluating the clinical importance of these covariates on steady-state indicated minimal changes on bromopride exposure. The mixed absorption model was reasonable to describe the absorption process of bromopride because it had the flexibility to fit multiple-peaks profile and shows good agreement with physicochemical properties of drug.

Published
2019

17. Model-Based Characterization of the Pharmacokinetics of Pembrolizumab: A Humanized Anti-PD-1 Monoclonal Antibody in Advanced Solid Tumors

Author

Marita Prohn, Tomoko Freshwater, Anna Georgieva Kondic, Claire Li, Jeroen Elassaiss-Schaap, Julie A. Stone, R de Greef, Malidi Ahamadi, and Dinesh P. de Alwis

Subjects
0301 basic medicine, Volume of distribution, Oncology, medicine.medical_specialty, education.field_of_study, business.industry, Population, Ipilimumab, Pembrolizumab, Pharmacology, Clinical trial, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Pharmacokinetics, 030220 oncology & carcinogenesis, Modeling and Simulation, Internal medicine, Monoclonal, medicine, Pharmacology (medical), Clinical significance, business, education, medicine.drug
Abstract

Pembrolizumab, a potent antibody against programmed death 1 (PD-1) receptor, has shown robust antitumor activity and manageable safety in patients with advanced solid tumors. Its pharmacokinetic (PK) properties were analyzed with population PK modeling using pooled data from the KEYNOTE-001, -002, and -006 studies of patients with advanced melanoma, non-small cell lung cancer (NSCLC), and other solid tumor types. Pembrolizumab clearance was low and the volume of distribution small, as is typical for therapeutic antibodies. Identified effects of sex, baseline Eastern Cooperative Oncology Group performance status, measures of renal and hepatic function, tumor type and burden, and prior ipilimumab treatment on pembrolizumab exposure were modest and lacked clinical significance. Furthermore, simulations demonstrated the model has robust power to detect clinically relevant covariate effects on clearance. These results support the use of the approved pembrolizumab dose of 2 mg/kg every 3 weeks without dose adjustment in a variety of patient subpopulations.

Published
2016
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18. Methods and strategies for assessing uncontrolled drug–drug interactions in population pharmacokinetic analyses: results from the International Society of Pharmacometrics (ISOP) Working Group

Author

Nageshwar Budha, Malidi Ahamadi, Peter L. Bonate, Mats O. Karlsson, Herbert Struemper, Janet R. Wade, Patanjali Ravva, Ana Ruiz-Garcia, Ying Hong, Justin C. Earp, and Amparo de la Peña

Subjects
Population, computer.software_genre, 030226 pharmacology & pharmacy, Outcome (game theory), 03 medical and health sciences, Clinical Trials, Phase II as Topic, 0302 clinical medicine, Covariate, Humans, Medicine, Drug Interactions, Set (psychology), education, Pharmacology, education.field_of_study, Actuarial science, business.industry, Mechanism (biology), Pharmacometrics, Drug class, Clinical Trials, Phase III as Topic, Pharmaceutical Preparations, Sample size determination, Sample Size, 030220 oncology & carcinogenesis, Data mining, business, computer
Abstract

The purpose of this work was to present a consolidated set of guidelines for the analysis of uncontrolled concomitant medications (ConMed) as a covariate and potential perpetrator in population pharmacokinetic (PopPK) analyses. This white paper is the result of an industry-academia-regulatory collaboration. It is the recommendation of the working group that greater focus be given to the analysis of uncontrolled ConMeds as part of a PopPK analysis of Phase 2/3 data to ensure that the resulting outcome in the PopPK analysis can be viewed as reliable. Other recommendations include: (1) collection of start and stop date and clock time, as well as dose and frequency, in Case Report Forms regarding ConMed administration schedule; (2) prespecification of goals and the methods of analysis, (3) consideration of alternate models, other than the binary covariate model, that might more fully characterize the interaction between perpetrator and victim drug, (4) analysts should consider whether the sample size, not the percent of subjects taking a ConMed, is sufficient to detect a ConMed effect if one is present and to consider the correlation with other covariates when the analysis is conducted, (5) grouping of ConMeds should be based on mechanism (e.g., PGP-inhibitor) and not drug class (e.g., beta-blocker), and (6) when reporting the results in a publication, all details related to the ConMed analysis should be presented allowing the reader to understand the methods and be able to appropriately interpret the results.

Published
2016
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19. Pembrolizumab: Role of Modeling and Simulation in Bringing a Novel Immunotherapy to Patients With Melanoma

Author

Mark S. Forman, Anna Georgieva Kondic, Manash Shankar Chatterjee, Dinesh P. de Alwis, R de Greef, Julie A. Stone, David C. Turner, D Cutler, Malidi Ahamadi, and Jeroen Elassaiss-Schaap

Subjects
0301 basic medicine, Oncology, medicine.medical_specialty, business.industry, medicine.medical_treatment, Melanoma, Cancer, Pembrolizumab, Immunotherapy, Pharmacology, medicine.disease, Clinical trial, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, 030220 oncology & carcinogenesis, Modeling and Simulation, Maximum tolerated dose, Internal medicine, medicine, Pharmacology (medical), business, Melanoma diagnosis
Abstract

Recently, immunotherapy has yielded promising results in several cancer types. Contrary to the established classical chemotherapy-dosing paradigm, a maximum tolerated dose approach does not always produce better clinical outcomes for novel targeted therapies, as their efficacy is frequently robust at pharmacologically active doses below the maximum tolerated dose. Integrated safety and efficacy assessments are needed to inform clinical dose and trial design, and to support an early identification of potentially safe and efficacious combination treatments.

Published
2016
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20. 31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016): part two

Author

Casey Ager, Matthew Reilley, Courtney Nicholas, Todd Bartkowiak, Ashvin Jaiswal, Michael Curran, Tina C. Albershardt, Anshika Bajaj, Jacob F. Archer, Rebecca S. Reeves, Lisa Y. Ngo, Peter Berglund, Jan ter Meulen, Caroline Denis, Hormas Ghadially, Thomas Arnoux, Fabien Chanuc, Nicolas Fuseri, Robert W. Wilkinson, Nicolai Wagtmann, Yannis Morel, Pascale Andre, Michael B. Atkins, Matteo S. Carlino, Antoni Ribas, John A. Thompson, Toni K. Choueiri, F. Stephen Hodi, Wen-Jen Hwu, David F. McDermott, Victoria Atkinson, Jonathan S. Cebon, Bernie Fitzharris, Michael B. Jameson, Catriona McNeil, Andrew G. Hill, Eric Mangin, Malidi Ahamadi, Marianne van Vugt, Mariëlle van Zutphen, Nageatte Ibrahim, Georgina V. Long, Robyn Gartrell, Zoe Blake, Ines Simoes, Yichun Fu, Takuro Saito, Yingzhi Qian, Yan Lu, Yvonne M. Saenger, Sadna Budhu, Olivier De Henau, Roberta Zappasodi, Kyle Schlunegger, Bruce Freimark, Jeff Hutchins, Christopher A. Barker, Jedd D. Wolchok, Taha Merghoub, Elena Burova, Omaira Allbritton, Peter Hong, Jie Dai, Jerry Pei, Matt Liu, Joel Kantrowitz, Venus Lai, William Poueymirou, Douglas MacDonald, Ella Ioffe, Markus Mohrs, William Olson, Gavin Thurston, Cristian Capasso, Federica Frascaro, Sara Carpi, Siri Tähtinen, Sara Feola, Manlio Fusciello, Karita Peltonen, Beatriz Martins, Madeleine Sjöberg, Sari Pesonen, Tuuli Ranki, Lukasz Kyruk, Erkko Ylösmäki, Vincenzo Cerullo, Fabio Cerignoli, Biao Xi, Garret Guenther, Naichen Yu, Lincoln Muir, Leyna Zhao, Yama Abassi, Víctor Cervera-Carrascón, Mikko Siurala, João Santos, Riikka Havunen, Suvi Parviainen, Akseli Hemminki, Angus Dalgleish, Satvinder Mudan, Mark DeBenedette, Ana Plachco, Alicia Gamble, Elizabeth W. Grogan, John Krisko, Irina Tcherepanova, Charles Nicolette, Pooja Dhupkar, Ling Yu, Eugenie S. Kleinerman, Nancy Gordon, Italia Grenga, Lauren Lepone, Sofia Gameiro, Karin M. 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Ostrowski, Madhuri Koti, Katrina Au, Nichole Peterson, Peter Truesdell, Gillian Reid-Schachter, Charles Graham, Andrew Craig, Julie-Ann Francis, Beatrix Kotlan, Timea Balatoni, Emil Farkas, Laszlo Toth, Mihaly Ujhelyi, Akos Savolt, Zoltan Doleschall, Szabolcs Horvath, Klara Eles, Judit Olasz, Orsolya Csuka, Miklos Kasler, Gabriella Liszkay, Eytan Barnea, Collin Blakely, Patrick Flynn, Reid Goodman, Raphael Bueno, David Sugarbaker, David Jablons, V. Courtney Broaddus, Brian West, Paul R. Kunk, Joseph M. Obeid, Kevin Winters, Patcharin Pramoonjago, Edward B. Stelow, Todd W. Bauer, Osama E. Rahma, Adam Lamble, Yoko Kosaka, Fei Huang, Kate A. Saser, Homer Adams, Christina E. Tognon, Ted Laderas, Shannon McWeeney, Marc Loriaux, Jeffery W. Tyner, Brian J. Druker, Evan F. Lind, Zhuqing Liu, Shanhong Lu, Lawrence P. Kane, Gulidanna Shayan, Julia Femel, Ryan Lane, Jamie Booth, Amanda W. Lund, Anthony Rodriguez, Victor H. Engelhard, Alessandra Metelli, Bill X. Wu, Caroline W. Fugle, Rachidi Saleh, Shaoli Sun, Jennifer Wu, Bei Liu, Zihai Li, Zachary S. Morris, Emily I. Guy, Clinton Heinze, Jasdeep Kler, Monica M. Gressett, Lauryn R. Werner, Stephen D. Gillies, Alan J. Korman, Hans Loibner, Jacquelyn A. Hank, Alexander L. Rakhmilevich, Paul M. Harari, Paul M. Sondel, Erica Huelsmann, Joseph Broucek, Dorothee Brech, Tobias Straub, Martin Irmler, Johannes Beckers, Florian Buettner, Elke Schaeffeler, Matthias Schwab, Elfriede Noessner, Alison Wolfreys, Andre Da Costa, John Silva, Andrea Crosby, Ludovicus Staelens, Graham Craggs, Annick Cauvin, Sean Mason, Alison M. Paterson, Andrew C. Lake, Caroline M. Armet, Rachel W. O’Connor, Jonathan A. Hill, Emmanuel Normant, Ammar Adam, Detlev M. Biniszkiewicz, Scott C. Chappel, Vito J. Palombella, Pamela M. Holland, Annette Becker, Manmohan R. Leleti, Eric Newcomb, Joanne B. L. Tan, Suthee Rapisuwon, Arash Radfar, Kellie Gardner, Geoffrey Gibney, Michael Atkins, Keith R. Rennier, Robert Crowder, Ping Wang, Russell K. Pachynski, Rosa M. Santana Carrero, Sarai Rivas, Figen Beceren-Braun, Scott Anthony, Kimberly S. Schluns, Deepali Sawant, Maria Chikina, Hiroshi Yano, Creg Workman, Elise Salerno, Ileana Mauldin, Donna Deacon, Sofia Shea, Joel Pinczewski, Thomas Gajewski, Stefani Spranger, Brendan Horton, Akiko Suzuki, Pamela Leland, Bharat H. Joshi, Raj K. Puri, Randy F. Sweis, Riyue Bao, Jason Luke, Marie-Nicole Theodoraki, Frances-Mary Mogundo, Haejung Won, Dayson Moreira, Chan Gao, Xingli Zhao, Priyanka Duttagupta, Jeremy Jones, Massimo D’Apuzzo, and Sumanta Pal

Subjects
0301 basic medicine, Pharmacology, Cancer Research, medicine.medical_specialty, business.industry, medicine.medical_treatment, Immunology, Cancer, Immunotherapy, medicine.disease, 3. Good health, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Oncology, 030220 oncology & carcinogenesis, Family medicine, Molecular Medicine, Immunology and Allergy, Medicine, business
Abstract

O1 IL-15 primes an mTOR-regulated gene-expression program to prolong anti-tumor capacity of human natural killer cells #### Andreas Lundqvist1, Vincent van Hoef1, Xiaonan Zhang1, Erik Wennerberg2, Julie Lorent1, Kristina Witt1, Laia Masvidal Sanz1, Shuo Liang1, Shannon Murray3, Ola Larsson1

Published
2016
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21. Prediction of the hERG potassium channel inhibition potential with use of artificial neural networks

Author

Malidi Ahamadi, Aleksander Mendyk, Barbara Winiowska, and Sebastian Polak

Subjects
Drug, Computer science, media_common.quotation_subject, Activation function, hERG, Machine learning, computer.software_genre, medicine.disease_cause, medicine, IC50, media_common, Virtual screening, Cardiotoxicity, biology, Artificial neural network, business.industry, In vitro, Clinical trial, Drug development, Lipophilicity, Toxicity, biology.protein, Artificial intelligence, business, computer, Software, Genotoxicity
Abstract

New drug development is a complex and time consuming process. The procedure is informally divided into strongly inter-dependent phases beginning from chemical structure synthesis or bioengineering through ADME-Tox properties assessment, clinical trials, up to the market introduction. Recently more and more effort has been invested in the early toxicity assessment of the drugs being developed. Apart from relatively well known and widely researched groups of effects which include hepatotoxicity, immunotoxicity, genotoxicity new toxic effects have become deeply investigated. One of the possible and potentially dangerous cardiotoxic effects is triggered by drugs acquired long QT syndrome (LQTS) which can lead to the fatal ventricular arrhythmia what effected in withdrawal of several drugs from the market. In most drugs known causing the ECG (electrocardiography) interferences the effect results from inhibition of the fast potassium channels (encoded as hERG follow the gene name-human ERG). Therefore early prediction of the hERG channel-drug interaction potential has become a major pharmacological safety concern. The objective of this research was to develop a reliable empirical model for the - triggered by drugs - potassium channel inhibition prediction with use of the previously published and publicly available database. The input data consisted of in vitro research settings, drug chemical structure (molecular fingerprints) and physico-chemical parameters for all substances present in database. Artificial neural networks were chosen as the algorithms for the models development and back-propagation multi-layer perceptrons as well as neuro-fuzzy systems of Mamdani MISO (multiple input single output) type were tested. Classifiers were built on the training set containing 447 records, describing 175 various chemicals. Two test procedures were applied for the model performance assessment: standard 10-fold cross validation procedure and validation based on the external test set containing 45 records describing. Various activation functions were tested including hyperbolic tangent, sigma and fsr function. The performance of the best model estimated in 10-fold CV was 76% (78% for positive and 74% for negative output respectively). Neural network model with 3 and 2 cells in hidden layers respectively and sigma activation function properly predicted 89% instances from the external validation dataset. By neural model analysis it was possible to estimate quantitative relationship between cardiotoxicity risk potential of particular drug and its lipophilicity described as the logP value.

Published
2011
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22. Numerical study of the rheology of rigid fillers suspended in long-chain branched polymer under planar extensional flow

Author

Malidi Ahamadi and Oliver G. Harlen

Subjects
Materials science, Applied Mathematics, Mechanical Engineering, General Chemical Engineering, Numerical analysis, Constitutive equation, Multiphase flow, Fluid mechanics, Mechanics, Condensed Matter Physics, Finite element method, Viscoelasticity, Rheology, Periodic boundary conditions, General Materials Science
Abstract

We report a detailed numerical study of the rheology of two-dimensional rigid fillers suspended in branched polymer melt under planar extensional flow. The polymer melt is modelled using the pom-pom constitutive equation. The numerical method uses a finite element solution of the flow in a unit cell within the self-replicating lattice for planar extensional flow identified by Kraynik and Reinelt [Int. J. Multiphase flow 18 (1992) 1045]. This is implemented using a quotient space representation that maps all points in space onto points within the unit cell. We show that the Kraynik and Reinelt cell allows simulations of suspensions under planar extensional flow to be conducted to large strains in a truly periodic cell. The influence of both the pom-pom parameters and the particle area fraction on the rheology of the suspension are investigated. We find a reduction in the degree of extension-rate thickening with the increase of both particles concentration and Weissenberg numbers in agreement with published experimental and numerical findings on other viscoelastic models. This reduction is found to be due to flow disturbance created by the particles which disrupts the alignment of backbone tube segments with the extensional axis.

Published
2010
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23. A Lagrangian finite element method for simulation of a suspension under planar extensional flow

Author

Malidi Ahamadi and Oliver G. Harlen

Subjects
Numerical Analysis, Physics and Astronomy (miscellaneous), Computer simulation, Delaunay triangulation, Applied Mathematics, Mathematical analysis, Multiphase flow, Fluid mechanics, Geometry, Finite element method, Computer Science Applications, Physics::Fluid Dynamics, Computational Mathematics, Modeling and Simulation, Newtonian fluid, Periodic boundary conditions, Boundary value problem, Mathematics
Abstract

A numerical simulation of a suspension of two-dimensional solid particles in a Newtonian fluid under planar extensional flow is presented. The method uses a finite element solution of the flow with a unit cell within the self-replicating lattice for planar extensional flow identified by Kraynik and Reinelt [A.M. Kraynik, D.A. Reinelt, Extensional motions of spatially periodic lattices, Int. J. Multiphase Flow 18 (1992) 1045]. This is implemented using a quotient space representation that maps all points space onto points within the unit cell. This mapping is preserved by using fully Lagrangian grid movement, with grid quality preserved by a combination of Delaunay reconnection and grid adaptivity. The no-slip boundary conditions on the particles are enforced weakly via a traction force acting as a Lagrange multiplier. The method allows simulations of suspensions under planar extensional flow to be conducted to large strains in a truly periodic cell. The method is illustrated for both isotropic and anisotropic two-dimensional particles and can be easily extended to viscoelastic fluids and to non-rigid particles.

Published
2008
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24. Prediction of concentration-time profile and its inter-individual variability following the dermal drug absorption

Author

Malidi Ahamadi, H Mishra, Masoud Jamei, Nikunjkumar Patel, Amin Rostami-Hodjegan, Cyrus Ghobadi, and Sebastian Polak

Subjects
Male, Diclofenac, In silico, Skin Absorption, Pharmaceutical Science, Simcyp$^{®}$ simulator, Absorption (skin), Computational biology, Pharmacology, Biology, Clinical pharmacokinetic, Administration, Cutaneous, Models, Biological, inter-individual variability, Pharmacokinetics, distribution, Humans, Computer Simulation, In vitro in vivo, Time profile, Skin, physiological model, integumentary system, Drug disposition, Anti-Inflammatory Agents, Non-Steroidal, transdermal drug delivery, Population variability, physiologically based pharmacokinetic (PBPK) models, ADME (absorption), excretion, in vitro–in vivo extrapolation (IVIVE), Female, metabolism, mathematical model
Abstract

Estimation of systemic exposure after absorption of any xenobiotic from the skin is very important in development of dermal pharmaceutical products as well as assessing un-intended exposures due to cosmetic products or environmental and occupational compounds. Historically, animal models have been used to evaluate dermal drug absorption before conducting human trials. However, occasional disparity between the animal and human data plus rising public interest and regulatory requirements to reduce animal usage in research combined with high cost and time-consuming attributes of animal experiments have prompted many academic and industrial researchers to develop economically viable and scientifically robust in silico and in vitro methods to assess dermal drug absorption. There are a number of in silico models available in literature from quantitative structure-activity relationship to semi-mechanistic to physiologically based mechanistic models. Nonetheless, to the best of our knowledge, so far, there has been no attempt to combine mechanistic skin absorption model with database of physiological variability to simulate the inter- and intra-individual variability observed in human trials. Thus, we report here mechanistic dermal absorption model with formulation, stratum corneum, viable epidermis-dermis and blood compartments along with datab"ase of human dermal physiological variability including gender, ethnic and site of application variations. The developed model is incorporated into the Simcyp simulator which is a 'bottom-up' platform and database for mechanistic modelling and simulation of the drug disposition process using full body physiologically based pharmacokinetics model. The built model is validated using the clinical pharmacokinetic data from five different topical formulations of diclofenac. The effect of penetration enhancers, site of application, gender and ethnic variations were incorporated to simulate the clinical trials. The applied mechanistic dermal absorption model when combined with skin physiological database was able to recover well the observed clinical pharmacokinetics and population variability in all the five validation studies.

Published
2012

26. Rheology Of Suspensions Derived From Numerical Simulation

Author

Oliver G. Harlen and Malidi Ahamadi

Subjects
Condensed Matter::Soft Condensed Matter, Physics::Fluid Dynamics, Simple shear, Materials science, Shear (geology), Computer simulation, Rheology, Numerical analysis, Rheometer, Strain hardening exponent, Composite material, Shear flow
Abstract

In many polymer processing applications filler particles such as glass beads are added to the polymer matrix. To study the rheology of such multiphase systems we perform direct simulations of the motion of the suspended particles when subjected to an external linear flow, such as simple shear or planar extensional flow. The method uses a Lagrangian finite element grid that deforms with fluid combined with a quotient representation of the periodic computational domain.For shear flow we show that one can predict the viscometric properties of the suspension for shear thining fluid by using a simple shifting model. For planar extensional flow it is found that adding particle suppressed the extend of strain hardening in strongly strain‐hardening fluids.

Published
2007
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27. 3344 Relationship between pembrolizumab exposure and efficacy/safety in 1016 patients (pts) with advanced or metastatic melanoma

Author

Soonmo Peter Kang, R de Greef, Kapil Mayawala, Scot Ebbinghaus, Anna Georgieva Kondic, Manash Shankar Chatterjee, Tomoko Freshwater, David C. Turner, Julie A. Stone, Jeroen Elassaiss-Schaap, Malidi Ahamadi, and Dinesh P. de Alwis

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Metastatic melanoma, business.industry, Internal medicine, Medicine, Pembrolizumab, business
Published
2015
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28. Population pharmacokinetic (popPK) model of pembrolizumab (pembro; MK-3475) in patients (pts) treated in KEYNOTE-001 and KEYNOTE-002

Author

Gregory M. Lubiniecki, Christian U. Blank, Adil Daud, Caroline Robert, Soonmo Peter Kang, Matteo S. Carlino, Amita Patnaik, Rik de Greef, Omid Hamid, Scot Ebbinghaus, Marianne van Vugt, Tara C. Gangadhar, F. Stephen Hodi, Anna Georgieva Kondic, Tomoko Freshwater, Antoni Ribas, Malidi Ahamadi, and Janice M. Mehnert

Subjects
Cancer Research, education.field_of_study, biology, business.industry, Immunogenicity, Population, Pembrolizumab, Pharmacology, Advanced cancer, Oncology, Pharmacokinetics, biology.protein, Medicine, In patient, Antibody, business, education
Abstract

3058 Background: The anti–PD-1 antibody pembro has efficacy in advanced cancer pts. We characterized pembro PK properties and quantified the effect of clinical factors on exposure. Immunogenicity w...

Published
2015
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32. Symbolic-numerical methods for the computation of normal forms of PDEs

Author

Malidi Ahamadi and Jean-Jacques Gervais

Subjects
Partial differential equation, Applied Mathematics, Numerical analysis, Mathematical analysis, MathematicsofComputing_NUMERICALANALYSIS, Symbolic computation, Normal forms, Finite element method, Computational Mathematics, Nonlinear system, Pitchfork bifurcation, Finite element, ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION, Applied mathematics, Center manifold, Linear equation, Mathematics
Abstract

The center manifold and the normal forms are effective tools for the study of local bifurcations occurring in evolution equations. The computation of the center manifold and the normal form amounts, after more or less complex algebraic transformations, to solve in a recursive way a hierarchy of linear equations. We present a method and computer programs for the computation of normal forms of some nonlinear parabolic PDEs. These computations are performed using the symbolic algebra system Maple, Matlab and exploiting the compatibility of these two systems. Here the linear equations to be solved are infinite dimensional and we use the finite element method for this purpose. The use of the finite element method allows to consider problems with complex shape domains. In our programs, Maple takes care of the algebraic manipulations delivering the set of linear equations to be solved and writes some parts of the Matlab code for their resolution. We give three applications: a pitchfork bifurcation in a semilinear parabolic equation, a Hopf bifurcation and a bifurcation to rotating and standing waves in a reaction–diffusion system.

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