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Mould D.R.,Projections Research Inc.
Clinical Pharmacology and Therapeutics | Year: 2012

Disease-progression models are useful tools in drug development. They increase the information obtained from clinical trials, improve study designs, and allow in silico evaluations of new treatment combinations and dose regimens. Disease-progression modeling can save time and strengthen "go/no-go" criteria. The use of meta-based modeling and the linking of disease progression to discrete clinical end points have improved the utility of this valuable approach. This article provides an overview of disease-progression evaluations using these new approaches. Source


Mould D.R.,Projections Research Inc.
Clinical Pharmacology and Therapeutics | Year: 2016

Monoclonal antibodies (mAbs) have improved clinical outcomes for many therapeutic indications. However, extensive between-subject variability (BSV) contributes to therapeutic failures through suboptimal exposure. Therapeutic drug monitoring (TDM) is routinely implemented for inflammatory diseases; improving outcomes and reducing treatment costs. BSV can be more extensive with anticancer mAbs. Clearance BSV is associated with patient factors and disease burden, suggesting that TDM could benefit anticancer mAbs, as was seen with inflammatory disease, however, there are many hurdles. © 2015 ASCPT. Source


Mould D.R.,Projections Research Inc.
Digestive Diseases | Year: 2015

Monoclonal antibodies (MAbs) exhibit complex pharmacokinetics (PK) and pharmacodynamics (PD, response) against tumor necrosis factor (TNF). Many factors impact anti-TNF MAb PK, altering MAb clearance and therefore the half-life: albumin, weight (particularly, obesity), disease (severity, stage and co-morbidities) and concomitant administration of immunosuppressants (e.g. methotrexate). These factors can alter MAb exposure, impacting on the likelihood of clinical response. Formation of anti-drug antibodies (ADAs) is another potential factor that can affect MAb PK. Factors impacting the likelihood of developing ADA are classified as patient-related (concomitant immunosuppressants, prior ADA against other anti-TNF MAb) or product-related (structure, manufacturing process, aggregate formation, route of administration and dosing regimen). Repeated episodic exposure can induce ADAs, shortening the effective treatment interval. Avoiding intervals where anti-TNF MAbs are non-measurable is important for efficacy and may delay onset of ADAs. Thus, patients whose factors predispose them to having faster clearance (or short half-life) such as severe disease, low albumin or high body weight may need shorter dose intervals to reduce the likelihood of intermittent exposure. ADAs can have no effect or can impact efficacy through MAb binding, thus inhibiting its function or potentially causing hypersensitivity reactions (PD). ADA can also increase MAb clearance (PK). Because of their impact on MAb clearance, ADAs have been linked to lower serum drug concentrations, potentially negatively impacting clinical response. ADAs have been reported for biologics in most therapeutic areas. ADAs are well documented in clinical studies due to the Food and Drug Administration and the European Medicines Agency recommendations regarding testing and impact of immunogenicity. Lastly, the dose metrics (e.g. mg vs. mg/kg) can cause issues as well. MAbs such as infliximab are dosed on a mg/kg basis, which commonly results in low concentrations in patients with low body weight. Conversely MAbs such as adalimumab are administered as a flat (mg) dose, which can result in low concentrations in high weight patients. © 2015 S. Karger AG, Basel. Source


Mould D.R.,Projections Research Inc.
Clinical Pharmacology and Therapeutics | Year: 2012

Modeling during drug development is routinely used to integrate subject-level information, evaluate response, and inform clinical trials. Model-based meta-analysis (MBMA) combines aggregate safety and efficacy results from many trials. Because MBMA is based on results from large numbers of subjects, it increases the power to precisely detect small but clinically significant effects, providing a basis for quantitative drug development decisions and reducing time and cost. This Commentary describes an overview of MBMA and its application during drug development. © 2012 American Society for Clinical Pharmacology and Therapeutics. Source


Liu P.,Pfizer | Mould D.R.,Projections Research Inc.
Antimicrobial Agents and Chemotherapy | Year: 2014

To assess the pharmacokinetics (PK) of voriconazole and anidulafungin in patients with invasive aspergillosis (IA) in comparison with other populations, sparse PK data were obtained for 305 adults from a prospective phase 3 study comparing voriconazole and anidulafungin in combination versus voriconazole monotherapy (voriconazole, 6 mg/kg intravenously [IV] every 12 h [q12h] for 24 h followed by 4 mg/kg IV q12h, switched to 300 mg orally q12h as appropriate; with placebo or anidulafungin IV, a 200-mg loading dose followed by 100 mg q24h). Voriconazole PK was described by a two-compartment model with first-order absorption and mixed linear and time-dependent nonlinear (Michaelis-Menten) elimination; anidulafungin PK was described by a two-compartment model with first-order elimination. For voriconazole, the normal inverse Wishart prior approach was implemented to stabilize the model. Compared to previous models, no new covariates were identified for voriconazole or anidulafungin. PK parameter estimates of voriconazole and anidulafungin are in agreement with those reported previously except for voriconazole clearance (the nonlinear clearance component became minimal). At a 4-mg/kg IV dose, voriconazole exposure tended to increase slightly as age, weight, or body mass index increased, but the difference was not considered clinically relevant. Estimated voriconazole exposures in IA patients at 4 mg/kg IV were higher than those reported for healthy adults (e.g., the average area under the curve over a 12-hour dosing interval [AUC 0-12] at steady state was 46% higher); while it is not definitive, age and concomitant medications may impact this difference. Estimated anidulafungin exposures in IA patients were comparable to those reported for the general patient population. This study was approved by the appropriate institutional review boards or ethics committees and registered on ClinicalTrials.gov (NCT00531479). Copyright © 2014, American Society for Microbiology. All Rights Reserved. Source

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