Ensuring diversity in clinical trials: The role of clinical pharmacology.

Increasing the diversity of participants in clinical trials is important as it allows further examination of drug effects in all subgroups of patients who will be prescribed an approved medicine. It also gives patients more confidence in the medicine when they know that individuals similar to themselves have participated in pivotal efficacy and safety trials. Pfizer recently committed to ensuring that its clinical trials reflect racial and ethnic demographics of the patient populations in the countries and communities in which the trials are conducted. This paper furthers Pfizer's commitment by declaring what Clinical Pharmacology (CP) can do to advance this goal and expand patient populations to include other groups such as pediatrics, elderly, and those with organ impairment. This includes steps such as: Pfizer Clinical Pharmacology commits to these actions, which create a framework for the CP Community to enable increased diversity among participants in clinical trials and improved dosing recommendations for all patient subgroups.

Exposure-Response Characterization of Tofacitinib Efficacy in Moderate to Severe Ulcerative Colitis: Results From Phase II and Phase III Induction and Maintenance Studies.

Tofacitinib is an oral small molecule JAK inhibitor for the treatment of ulcerative colitis. Relationships between plasma tofacitinib concentration and efficacy were characterized using exposure-response (E-R) models, with demographic and disease covariates evaluated as potential predictors of efficacy. Data were from phase II and III (OCTAVE Induction 1 and 2) induction studies, and a phase III maintenance study (OCTAVE Sustain). Induction studies included 1,355 patients (tofacitinib 0.5, 3, 10, or 15 mg b.i.d. or placebo). The maintenance study included 592 patients (tofacitinib 5 or 10 mg b.i.d. or placebo). E-R models, including induction patients predicted placebo-adjusted remission rates of 6.4% and 12.7% at week 8 for tofacitinib 5 and 10 mg b.i.d., respectively; corresponding rates in patients without prior tumor necrosis factor inhibitor (TNFi) failure were 12.8% and 20.4%. Estimates to achieve/maintain remission at week 52 of maintenance were 29% and 18% (tofacitinib 5 mg b.i.d.), and 41% and 26% (tofacitinib 10 mg b.i.d.), for patients in remission or not following induction, respectively. During maintenance, patients with prior TNFi failure had lower probability of remission on 5 mg b.i.d. (24.9%) than 10 mg b.i.d. (35.0%). Results indicated tofacitinib 10 mg b.i.d. was an appropriate induction dose but suggested efficacy with 5 mg b.i.d. in patients without prior TNFi failure. Tofacitinib 5 mg b.i.d. was efficacious for maintenance, although patients with prior TNFi failure might see additional benefit on 10 mg b.i.d. Per product labeling, recommended tofacitinib induction dose is 10 mg b.i.d., then maintenance at 5 mg b.i.d. For patients who lose response during maintenance, 10 mg b.i.d. may be considered, limited to the shortest duration. Clinicaltrials.gov: NCT00787202; NCT01465763; NCT01458951; and NCT01458574.

Correction to: Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products.

A Correction to this paper has been published: https://doi.org/10.1208/s12248-020-00534-0.

Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products.

Decision-making in drug development benefits from an integrated systems approach, where the stakeholders identify and address the critical questions for the system through carefully designed and performed studies. Biopharmaceutics Risk Assessment Roadmap (BioRAM) is such a systems approach for application of systems thinking to patient focused and timely decision-making, suitable for all stages of drug discovery and development. We described the BioRAM therapy-driven drug delivery framework, strategic roadmap, and integrated risk assessment instrument (BioRAM Scoring Grid) in previous publications (J Pharm Sci 103:3377-97, 2014; J Pharm Sci 105:3243-55, 2016). Integration of systems thinking with pharmaceutical development, manufacturing, and clinical sciences and health care is unique to BioRAM where the developed strategy identifies the system and enables risk characterization and balancing for the entire system. Successful decision-making process in BioRAM starts with the Blueprint (BP) meetings. Through shared understanding of the system, the program strategy is developed and captured in the program BP. Here, we provide three semi-hypothetical examples for illustrating risk-based decision-making in high and moderate risk settings. In the high-risk setting, which is a rare disease area, two completely alternate development approaches are considered (gene therapy and small molecule). The two moderate-risk examples represent varied knowledge levels and drivers for the programs. In one moderate-risk example, knowledge leveraging opportunities are drawn from the manufacturing knowledge and clinical performance of a similar drug substance. In the other example, knowledge on acute tolerance patterns for a similar mechanistic pathway is utilized for identifying markers to inform the drug release profile from the dosage form with the necessary "flexibility" for dosing. All examples illustrate implementation of the BioRAM strategy for leveraging knowledge and decision-making to optimize the clinical performance of drug products for patient benefit.

ITC Commentary on Metformin Clinical Drug-Drug Interaction Study Design That Enables an Efficacy- and Safety-Based Dose Adjustment Decision.

Metformin drug-drug interaction (DDI) studies are conducted during development of drugs that inhibit organic cation transporters and/or multidrug and toxin extrusion proteins (OCTs/MATEs). Monitoring solely changes in systemic exposure, the typical DDI study endpoint appears inadequate for metformin, which is metabolically stable, has poor passive membrane permeability, and undergoes transporter-mediated tissue distribution and clearance. Evaluation of renal clearance, antihyperglycemic effects, and potentially lactate as an exploratory safety marker, can support rational metformin dose adjustment. The proposed DDI study design aims to adequately inform metformin dosing during comedication.

Optimizing Clinical Drug Product Performance: Applying Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid.

The aim of Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid is to facilitate optimization of clinical performance of drug products. BioRAM strategy relies on therapy-driven drug delivery and follows an integrated systems approach for formulating and addressing critical questions and decision-making (J Pharm Sci. 2014,103(11): 3777-97). In BioRAM, risk is defined as not achieving the intended in vivo drug product performance, and success is assessed by time to decision-making and action. Emphasis on time to decision-making and time to action highlights the value of well-formulated critical questions and well-designed and conducted integrated studies. This commentary describes and illustrates application of the BioRAM Scoring Grid, a companion to the BioRAM strategy, which guides implementation of such an integrated strategy encompassing 12 critical areas and 6 assessment stages. Application of the BioRAM Scoring Grid is illustrated using published literature. Organizational considerations for implementing BioRAM strategy, including the interactions, function, and skillsets of the BioRAM group members, are also reviewed. As a creative and innovative systems approach, we believe that BioRAM is going to have a broad-reaching impact, influencing drug development and leading to unique collaborations influencing how we learn, and leverage and share knowledge.

Breast cancer resistance protein (ABCG2) in clinical pharmacokinetics and drug interactions: practical recommendations for clinical victim and perpetrator drug-drug interaction study design.

Breast cancer resistance protein (BCRP; ABCG2) limits intestinal absorption of low-permeability substrate drugs and mediates biliary excretion of drugs and metabolites. Based on clinical evidence of BCRP-mediated drug-drug interactions (DDIs) and the c.421C>A functional polymorphism affecting drug efficacy and safety, both the US Food and Drug Administration and European Medicines Agency recommend preclinical evaluation and, when appropriate, clinical assessment of BCRP-mediated DDIs. Although many BCRP substrates and inhibitors have been identified in vitro, clinical translation has been confounded by overlap with other transporters and metabolic enzymes. Regulatory recommendations for BCRP-mediated clinical DDI studies are challenging, as consensus is lacking on the choice of the most robust and specific human BCRP substrates and inhibitors and optimal study design. This review proposes a path forward based on a comprehensive analysis of available data. Oral sulfasalazine (1000 mg, immediate-release tablet) is the best available clinical substrate for intestinal BCRP, oral rosuvastatin (20 mg) for both intestinal and hepatic BCRP, and intravenous rosuvastatin (4 mg) for hepatic BCRP. Oral curcumin (2000 mg) and lapatinib (250 mg) are the best available clinical BCRP inhibitors. To interrogate the worst-case clinical BCRP DDI scenario, study subjects harboring the BCRP c.421C/C reference genotype are recommended. In addition, if sulfasalazine is selected as the substrate, subjects having the rapid acetylator phenotype are recommended. In the case of rosuvastatin, subjects with the organic anion-transporting polypeptide 1B1 c.521T/T genotype are recommended, together with monitoring of rosuvastatin's cholesterol-lowering effect at baseline and DDI phase. A proof-of-concept clinical study is being planned by a collaborative consortium to evaluate the proposed BCRP DDI study design.

The biopharmaceutics risk assessment roadmap for optimizing clinical drug product performance.

The biopharmaceutics risk assessment roadmap (BioRAM) optimizes drug product development and performance by using therapy-driven target drug delivery profiles as a framework to achieve the desired therapeutic outcome. Hence, clinical relevance is directly built into early formulation development. Biopharmaceutics tools are used to identify and address potential challenges to optimize the drug product for patient benefit. For illustration, BioRAM is applied to four relatively common therapy-driven drug delivery scenarios: rapid therapeutic onset, multiphasic delivery, delayed therapeutic onset, and maintenance of target exposure. BioRAM considers the therapeutic target with the drug substance characteristics and enables collection of critical knowledge for development of a dosage form that can perform consistently for meeting the patient's needs. Accordingly, the key factors are identified and in vitro, in vivo, and in silico modeling and simulation techniques are used to elucidate the optimal drug delivery rate and pattern. BioRAM enables (1) feasibility assessment for the dosage form, (2) development and conduct of appropriate "learning and confirming" studies, (3) transparency in decision-making, (4) assurance of drug product quality during lifecycle management, and (5) development of robust linkages between the desired clinical outcome and the necessary product quality attributes for inclusion in the quality target product profile.

Summary workshop report: Facilitating oral product development and reducing regulatory burden through novel approaches to assess bioavailability/bioequivalence.

This summary workshop report highlights presentations and over-arching themes from an October 2011 workshop. Discussions focused on best practices in the application of biopharmaceutics in oral drug product development and evolving bioequivalence approaches. Best practices leverage biopharmaceutic data and other drug, formulation, and patient/disease data to identify drug development challenges in yielding a successfully performing product. Quality by design and product developability paradigms were discussed. Development tools include early development strategies to identify critical absorption factors and oral absorption modeling. An ongoing theme was the desire to comprehensively and systematically assess risk of product failure via the quality target product profile and root cause and risk analysis. However, a parallel need is reduced timelines and fewer resources. Several presentations discussed applying Biopharmaceutics Classification System (BCS) and in vitro-in vivo correlations in development and in post-development and discussed both resource savings and best scientific practices. The workshop also focused on evolving bioequivalence approaches, with emphasis on highly variable products (HVDP), as well as specialized modified-release products. In USA, two bioequivalence approaches for HVDP are the reference-scaled average bioequivalence approach and the two-stage group-sequential design. An adaptive sequential design approach is also acceptable in Canada. In European Union, two approaches for HVDP are a two-stage design and an approach to widen C (max) acceptance limits. For some specialized modified-release products, FDA now requests partial area under the curve. Rationale and limitations of such metrics were discussed (e.g., zolpidem and methylphenidate). A common theme was the benefit of the scientific and regulatory community developing, validating, and harmonizing newer bioequivalence methodologies (e.g., BCS-based waivers and HVDP trial designs).

Development strategies for IVIVC in an industrial environment.

Product development is typically challenging. There is a strong desire to understand critical performance factors early in order to optimize formulations for Phase III trials or marketing approval. However, over 90% of drugs entering development in humans do not make it to the market. Thus there is a tremendous risk that resources spent early in development will be wasted as candidates attrite. To overcome this apparent dilemma, a Bayesian approach is suggested. In 'traditional' product development, clinical study designs are typically relatively assumption free and often do not consider learning from earlier investigations. A Bayesian approach is one in which prior information is considered when interpreting the results of the current study. A candidate IVIVC can be developed at the earliest stage of clinical development. Subsequently there are multiple opportunities within a typical development program to assess the performance of the preliminary IVIVC as new formulations are introduced. With each introduction, there is an opportunity to either confirm the adequacy of the IVIVC or to identify the need for development of a more predictive dissolution test and IVIVC.

A technique to estimate in vivo dissolution profiles without data from a solution.

Dissolution tests are expected to ensure adequate in vivo product performance. Given the recent progress in the ability to predict of human permeability, it is possible to synthesize the plasma drug concentration-time profile from human permeability predictions and the results of the first-in-human trial and use these data to synthesize a pharmacokinetic profile for a solution and provide an initial estimate of the in vivo dissolution profile. This manuscript provides details of such a deconvolution methodology in order to provide an initial estimate of in vivo dissolution. Plasma metoprolol concentration-time data from a previously published study examining the pharmacokinetics of three metoprolol formulations (100 mg), slow, moderate, and fast releasing, and an oral solution (50 mg) were used to estimate in vitro dissolution profiles. A one-compartment unit impulse function was used, and the absorption rate was estimated from animal permeability data (synthetic solution method). The results were compared to those obtained using a unit impulse function estimated from the oral solution data. In vivo dissolution profiles estimated from animal permeability data were similar to those estimated from the oral solution data. Ratios of absorption rate constants (synthetic solution method/oral solution) ranged from 1 to 1.3. The synthetic solution method offers a way to estimate in vivo dissolution profile through deconvolution. It is applicable in cases where it is not possible or feasible to obtain data from a solution. It performs best in cases where dissolution is the rate-limiting step in the absorption process.

Impact of Biopharmaceutics Classification System-based biowaivers.

The Biopharmaceutics Classification System (BCS) is employed to waive in vivo bioequivalence testing (i.e. provide "biowaivers") for new and generic drugs that are BCS class I. Granting biowaivers under systems such as the BCS eliminates unnecessary drug exposures to healthy subjects and provides economic relief, while maintaining the high public health standard for therapeutic equivalence. International scientific consensus suggests class III drugs are also eligible for biowaivers. The objective of this study was to estimate the economic impact of class I BCS-based biowaivers, along with the economic impact of a potential expansion to BCS class III. Methods consider the distribution of drugs across the four BCS classes, numbers of in vivo bioequivalence studies performed from a five year period, and effects of highly variable drugs (HVDs). Results indicate that 26% of all drugs are class I non-HVDs, 7% are class I HVDs, 27% are class III non-HVDs, and 3% are class III HVDs. An estimated 66 to 76 million dollars can be saved each year in clinical study costs if all class I compounds were granted biowaivers. Between 21 and 24 million dollars of this savings is from HVDs. If BCS class III compounds were also granted waivers, an additional direct savings of 62 to 71 million dollars would be realized, with 9 to 10 million dollars coming from HVDs.

Meeting report: applied biopharmaceutics and quality by design for dissolution/release specification setting: product quality for patient benefit.

A biopharmaceutics and Quality by Design (QbD) conference was held on June 10-12, 2009 in Rockville, Maryland, USA to provide a forum and identify approaches for enhancing product quality for patient benefit. Presentations concerned the current biopharmaceutical toolbox (i.e., in vitro, in silico, pre-clinical, in vivo, and statistical approaches), as well as case studies, and reflections on new paradigms. Plenary and breakout session discussions evaluated the current state and envisioned a future state that more effectively integrates QbD and biopharmaceutics. Breakout groups discussed the following four topics: Integrating Biopharmaceutical Assessment into the QbD Paradigm, Predictive Statistical Tools, Predictive Mechanistic Tools, and Predictive Analytical Tools. Nine priority areas, further described in this report, were identified for advancing integration of biopharmaceutics and support a more fundamentally based, integrated approach to setting product dissolution/release acceptance criteria. Collaboration among a broad range of disciplines and fostering a knowledge sharing environment that places the patient's needs as the focus of drug development, consistent with science- and risk-based spirit of QbD, were identified as key components of the path forward.

P-glycoprotein related drug interactions: clinical importance and a consideration of disease states.

IMPORTANCE OF THE FIELD: P-glycoprotein (P-gp) is the most characterized drug transporter in terms of its clinical relevance for pharmacokinetic disposition and interaction with other medicines. Clinically significant P-gp related drug interactions appear restricted to digoxin. P-gp may act as a major barrier to current and effective drug treatment in a number of diseases including cancer, AIDS, Alzheimer's and epilepsy due to its expression in tumors, lymphocytes, cell membranes of brain capillaries and the choroid plexus. AREAS COVERED IN THIS REVIEW: This review summarizes the current understanding of P-gp structure/function, clinical importance of P-gp related drug interactions and the modulatory role this transporter may contribute towards drug efficacy in disease states such as cancer, AIDS, Alzheimer's and epilepsy. WHAT THE READER WILL GAIN: The reader will gain an understanding that the clinical relevance of P-gp in drug interactions is limited. In certain disease states, P-gp in barrier tissues can modulate changes in regional distribution. TAKE HOME MESSAGE: P-gp inhibition in isolation will not result in clinically important alterations in systemic exposure; however, P-gp transport may be of significance in barrier tissues (tumors, lymphocytes, brain) resulting in attenuated efficacy.

Refining the in vitro and in vivo critical parameters for P-glycoprotein, [I]/IC50 and [I2]/IC50, that allow for the exclusion of drug candidates from clinical digoxin interaction studies.

The objective of this work was to further investigate the reasons for disconcordant clinical digoxin drug interactions (DDIs) particularly for false negative where in vitro data suggests no P-glycoprotein (P-gp) related DDI but a clinically relevant DDI is evident. Applying statistical analyses of binary classification and receiver operating characteristic (ROC), revised cutoff values for ratio of [I]/IC(50) < 0.1 and [I(2)]/IC(50) < 5 were identified to minimize the error rate, a reduction of false negative rate to 9% from 36% (based on individual ratios). The steady state total C(max) at highest dose of the inhibitor is defined as [I] and the ratio of the nominal maximal gastrointestinal concentration determined for highest dose per 250 mL volume defined [I(2)](.) We also investigated the reliability of the clinical data to see if recommendations can be made on values that would allow predictions of 25% change in digoxin exposure. The literature derived clinical digoxin interaction studies were statistically powered to detect relevant changes in exposure associated with digitalis toxicities. Our analysis identified that many co-meds administered with digoxin are cardiovascular (CV) agents. Moreover, our investigations also suggest that the presence of CV agents may alter cardiac output and/or kidney function that may act alone or are additional components to enhance digoxin exposure along with P-gp interaction. While we recommend digoxin as the probe substrate to define P-gp inhibitory potency for clinical assessment, we observed high concordance in P-gp inhibitory potency for calcein AM as a probe substrate.

Summary workshop report: bioequivalence, biopharmaceutics classification system, and beyond.

The workshop "Bioequivalence, Biopharmaceutics Classification System, and Beyond" was held May 21-23, 2007 in North Bethesda, MD, USA. This workshop provided an opportunity for pharmaceutical scientists to discuss the FDA guidance on the Biopharmaceutics Classification System (BCS), bioequivalence of oral products, and related FDA initiatives such as the FDA Critical Path Initiative. The objective of this Summary Workshop Report is to document the main points from this workshop. Key highlights of the workshop were (a) the described granting of over a dozen BCS-based biowaivers by the FDA for Class I drugs whose formulations exhibit rapid dissolution, (b) continued scientific support for biowaivers for Class III compounds whose formulations exhibit very rapid dissolution, (c) scientific support for a number of permeability methodologies to assess BCS permeability class, (d) utilization of BCS in pharmaceutical research and development, and (e) scientific progress in in vitro dissolution methods to predict dosage form performance.

Lack of a pharmacokinetic interaction between azithromycin and chloroquine.

A study was conducted to investigate a possible pharmacokinetic interaction between azithromycin and chloroquine. Twenty-four subjects received azithromycin, 1,000 mg a day for three days, followed by a washout period, then azithromycin, 1,000 mg plus chloroquine 600 mg base on days 1 and 2, and azithromycin, 1,000 mg plus chloroquine 300 mg base on day 3 of the final period. A second group of 16 subjects received chloroquine, 600 mg base on days 1 and 2, then 300 mg base on day 3. Blood samples were obtained serially up to 624 hours after the day 3 dose in each period. Log transformed maximum concentration and area under the curve values of azithromycin and chloroquine were compared using 90% confidence intervals calculated from appropriate analysis of variance models. Ninety percent confidence intervals for all pharmacokinetic parameters were contained within the interval 80-125%, which indicates the absence of a clinically relevant pharmacokinetic interaction.

The use of clinical trial simulation to support dose selection: application to development of a new treatment for chronic neuropathic pain.

PURPOSE: Pregabalin is being evaluated for the treatment of neuropathic pain. Two phase 2 studies were simulated to determine how precisely the dose that caused a one-point reduction in the pain score could be estimated. The likelihood of demonstrating at least a one-point change for each available dose strength was also calculated. METHODS: A pharmacokinetic-pharmacodynamic (PK/PD) model relating pain relief to gabapentin plasma concentrations was derived from a phase 3 study. The PK component of the model was modified to reflect pregabalin PK. The PD component was modified by scaling the gabapentin concentration-effect relationship to reflect pregabalin potency, which was based on preclincal data. Uncertainty about the potency difference and the steepness of the concentration-response slope necessitated simulating a distribution of outcomes for a series of PK/PD models. RESULTS: Analysis of the simulated data suggested that after accounting for the uncertainty, there was an 80% chance that the dose defining the clinical feature was within 45% of the true value. The likelihood of estimating a dose that was within an acceptable predefined precision range relative to a known value approximated 60%. The minimum dose that should be studied to have a reasonable chance of estimating the dose that caused a one-point change was 300 mg. CONCLUSIONS: Doses that identify predefined response may be imprecisely estimated, suggesting that replication of a similar outcome may be elusive in a confirmatory study. Quantification of this precision provides a rationale for phase 2 trial design and dose selection for confirmatory studies.