Demonstrating Bioequivalence for Two Dose Strengths of Niraparib and Abiraterone Acetate Dual-Action Tablets Versus Single Agents: Utility of Clinical Study Data Supplemented with Modeling and Simulation

BACKGROUND AND OBJECTIVE

The combination of niraparib and abiraterone acetate (AA) plus prednisone is under investigation for the treatment of patients with metastatic castration-resistant prostate cancer (mCRPC) and metastatic castration-sensitive prostate cancer (mCSPC). Regular-strength (RS) and lower-strength (LS) dual-action tablets (DATs), comprising niraparib 100 mg/AA 500 mg and niraparib 50 mg/AA 500 mg, respectively, were developed to reduce pill burden and improve patient experience. A bioequivalence (BE)/bioavailability (BA) study was conducted under modified fasting conditions in patients with mCRPC to support approval of the DATs.

METHODS

This open-label randomized BA/BE study (NCT04577833) was conducted at 14 sites in the USA and Europe. The study had a sequential design, including a 21-day screening phase, a pharmacokinetic (PK) assessment phase comprising three periods [namely (1) single-dose with up to 1-week run-in, (2) daily dose on days 1-11, and (3) daily dose on days 12-22], an extension where both niraparib and AA as single-agent combination (SAC; reference) or AA alone was continued from day 23 until discontinuation, and a 30-day follow-up phase. Patients were randomly assigned in a parallel-group design (four-sequence randomization) to receive a single oral dose of niraparib 100 mg/AA 1000 mg as a LS-DAT or SAC in period 1, and patients continued as randomized into a two-way crossover design during periods 2 and 3 where they received niraparib 200 mg/AA 1000 mg once daily as a RS-DAT or SAC. The design was powered on the basis of crossover assessment of RS-DAT versus SAC. During repeated dosing (periods 2 and 3, and extension phase), all patients also received prednisone/prednisolone 5 mg twice daily. Plasma samples were collected for measurement of niraparib and abiraterone plasma concentrations. Statistical assessment of the RS-DAT and LS-DAT versus SAC was performed on log-transformed pharmacokinetic parameters data from periods 2 and 3 (crossover) and from period 1 (parallel), respectively. Additional paired analyses and model-based bioequivalence assessments were conducted to evaluate the similarity between the LS-DAT and SAC.

RESULTS

For the RS-DAT versus SAC, the 90% confidence intervals (CI) of geometric mean ratios (GMR) for maximum concentration at a steady state (Cmax,ss) and area under the plasma concentration-time curve from 0-24 h at a steady state (AUC 0-24h,ss) were respectively 99.18-106.12% and 97.91-104.31% for niraparib and 87.59-106.69 and 86.91-100.23% for abiraterone. For the LS-DAT vs SAC, the 90% CI of GMR for AUC0-72h of niraparib was 80.31-101.12% in primary analysis, the 90% CI of GMR for Cmax,ss and AUC 0-24h,ss of abiraterone was 85.41-118.34% and 86.51-121.64% respectively, and 96.4% of simulated LS-DAT versus SAC BE trials met the BE criteria for both niraparib and abiraterone.

CONCLUSIONS

The RS-DAT met BE criteria (range 80%-125%) versus SAC based on 90% CI of GMR for Cmax,ss and AUC 0-24h,ss. The LS-DAT was considered BE to SAC on the basis of the niraparib component meeting the BE criteria in the primary analysis for AUC 0-72h; abiraterone meeting the BE criteria in additional paired analyses based on Cmax,ss and AUC 0-24h,ss; and the percentage of simulated LS-DAT versus SAC BE trials meeting the BE criteria for both.

CLINICALTRIALS

GOV IDENTIFIER

NCT04577833.

Determination and Confirmation of Recommended Ph2 Dose of Amivantamab in Epidermal Growth Factor Receptor Exon 20 Insertion Non-Small Cell Lung Cancer

Amivantamab has demonstrated durable responses with a tolerable safety profile in non-small cell lung cancer with EGFR exon 20 insertions (Ex20ins) who progressed after prior platinum chemotherapy. Data supporting the amivantamab recommended phase II dose (RP2D) in this patient population are presented. Pharmacokinetic (PK) analysis and population PK (PopPK) modeling were conducted using serum concentration data obtained following amivantamab intravenous administration (140-1,750 mg). Pharmacodynamics (PDs) were evaluated using depletion of soluble EGFR and MET. Exposure-response (E-R) analyses were performed using the primary efficacy end point of objective response rate in patients with EGFR Ex20ins. The E-R relationship for safety was explored for adverse events of clinical interest. Amivantamab exhibited linear PKs at 350-1,750 mg dose levels following administration, with no maximum tolerated dose identified. A two-compartment PopPK model with linear clearance adequately described the observed PKs. Body weight was a covariate of clearance and volume of distribution in the central compartment. PopPK modeling showed that a weight-based, 2-tier (< 80 and ≥ 80 kg) dosing strategy reduces PK variability and provides comparable exposure across 2 weight groups, with 87% of patients achieving exposures above the target threshold. The final confirmed RP2D of amivantamab was 1,050 mg for < 80 kg (1,400 mg for ≥ 80 kg) weekly in cycle 1 (28 days) and every 2 weeks thereafter. No significant exposure-efficacy or safety correlation was observed. In conclusion, the amivantamab RP2D is supported by PK, PD, safety, and efficacy analyses. E-R analyses confirmed that the current regimen provides durable efficacy with tolerable safety.

Practical dosing guidance for the management of clinician-administered injections of long-acting cabotegravir and rilpivirine

Cabotegravir (CAB) and rilpivirine (RPV) is the first complete long-acting (LA) injectable regimen recommended by treatment guidelines for the maintenance of HIV-1 virologic suppression in people with HIV-1 who are virologically suppressed on a stable antiretroviral regimen that is administered monthly (Q1M) or every 2 months (Q2M). As an alternative regimen to lifelong daily oral antiretroviral therapy, Q1M or Q2M dosing schedules are associated with increased patient satisfaction and treatment preference. In addition, it may address challenges associated with daily oral dosing, including fear of treatment disclosure or stigma, anxiety related to oral dosing adherence, and the daily reminder of HIV disease status. Cabotegravir + RPV LA is administered by clinical staff as two intramuscular injections dosed Q1M or Q2M. In this review, we share practical dosing guidance for CAB+RPV LA injectable therapy, including how to initiate therapy, schedule injection visits, manage dosing interruptions due to missed or delayed injection visits, manage errors in dosing, and transition to alternative antiretroviral therapy after discontinuation. Practical guidance on the clinical management of CAB+RPV LA dosing, including a detailed discussion using case-based scenarios that may be encountered in clinical practice, is provided. The clinician-administered CAB+RPV LA regimen has dosing management considerations that are flexible and considerate of the patient and has the potential to provide a highly desirable and efficacious alternative to daily oral antiretroviral therapy for many people with HIV-1.

Long-term safety and tolerability of atabecestat (JNJ-54861911), an oral BACE1 inhibitor, in early Alzheimer's disease spectrum patients: a randomized, double-blind, placebo-controlled study and a two-period extension study

Background

Atabecestat, a potent brain-penetrable inhibitor of BACE1 activity that reduces CSF amyloid beta (Aβ), was developed for oral treatment for Alzheimer’s disease (AD).

The long-term safety and effect of atabecestat on cognitive performance in participants with predementia AD in two phase 2 studies were assessed.

Methods

In the placebo-controlled double-blind parent ALZ2002 study, participants aged 50 to 85 years were randomized (1:1:1) to placebo or atabecestat 10 or 50 mg once daily (later reduced to 5 and 25 mg) for 6 months. Participants entered ALZ2004, a 12-month treatment extension with placebo or atabecestat 10 or 25 mg, followed by an open-label phase. Safety, changes in CSF biomarker levels, brain volume, and effects on cognitive performance were assessed.

Results

Of 114 participants randomized in ALZ2002, 99 (87%) completed, 90 entered the ALZ2004 double-blind phase, and 77 progressed to the open-label phase. CSF Aβ fragments and sAPPβ were reduced dose-proportionately. Decreases in whole brain and hippocampal volumes were greater in participants with mild cognitive impairment (MCI) due to AD than in preclinical AD, but were not affected by treatment. In ALZ2004, change from baseline in RBANS trended toward worse scores for atabecestat versus placebo. Elevated liver enzyme adverse events reported in 12 participants on atabecestat resulted in dosage modification and increased frequency of safety monitoring. Treatment discontinuation normalized ALT or AST in all except one with pretreatment elevation, which remained mildly elevated. No case met ALT/AST > 3× ULN and total bilirubin > 2× ULN (Hy’s law).

Conclusion

Atabecestat was associated with trend toward declines in cognition, and elevation of liver enzymes.

Trial registration

ALZ2002: ClinicalTrials.gov, NCT02260674, registered October 9, 2014; ALZ2004: ClinicalTrials.gov, NCT02406027, registered April 1, 2015.

Bayesian sequential integration within a preclinical pharmacokinetic and pharmacodynamic modeling framework: Lessons learned

The present manuscript aims to discuss the implications of sequential knowledge integration of small preclinical trials in a Bayesian pharmacokinetic and pharmacodynamic (PK-PD) framework. While, at first sight, a Bayesian PK-PD framework seems to be a natural framework to allow for sequential knowledge integration, the scope of this paper is to highlight some often-overlooked challenges while at the same time providing some guidances in the many and overwhelming choices that need to be made. Challenges as well as opportunities will be discussed that are related to the impact of (1) the prior specification, (2) the choice of random effects, (3) the type of sequential integration method. In addition, it will be shown how the success of a sequential integration strategy is highly dependent on a carefully chosen experimental design when small trials are analyzed.

Pharmacodynamics of atabecestat (JNJ-54861911), an oral BACE1 inhibitor in patients with early Alzheimer's disease: randomized, double-blind, placebo-controlled study

BACKGROUND

β-Secretase enzyme (BACE) inhibition has been proposed as a priority treatment mechanism for Alzheimer's disease (AD), but treatment initiation may need to be very early. We present proof of mechanism of atabecestat (also known as JNJ-54861911), an oral BACE inhibitor for the treatment of AD, in Caucasian and Japanese populations with early AD who do not show signs of dementia.

METHODS

In two similarly designed phase I studies, a sample of amyloid-positive elderly patients comprising 45 Caucasian patients with early AD diagnosed as preclinical AD (n = 15, Clinical Dementia Rating [CDR] = 0) or with mild cognitive impairment due to AD (n = 30, CDR = 0.5) and 18 Japanese patients diagnosed as preclinical AD (CDR-J = 0) were randomized 1:1:1 to atabecestat 10 or 50 mg or placebo (n = 6-8/treatment) daily for 4 weeks. Safety, pharmacokinetics (PK), and pharmacodynamics (PD) (i.e., reduction of cerebrospinal fluid [CSF] amyloid beta 1-40 [Aβ_1-40] levels [primary endpoint] and effect on other AD biomarkers) of atabecestat were evaluated.

RESULTS

In both populations, atabecestat was well tolerated and characterized by linear PK and high central nervous system penetrance of unbound drug. Atabecestat significantly reduced CSF Aβ_1-40 levels from baseline at day 28 in both the 10-mg (67-68%) and 50-mg (87-90%) dose groups compared with placebo. For Caucasians with early AD, the least squares mean differences (95% CI) were - 69.37 (- 72.25; - 61.50) and - 92.74 (- 100.08; - 85.39), and for Japanese with preclinical AD, they were - 62.48 (- 78.32; - 46.64) and - 80.81 (- 96.13; - 65.49), respectively. PK/PD model simulations confirmed that once-daily 10 mg and 50 mg atabecestat can attain 60-70% and 90% Aβ_1-40 reductions, respectively. The trend of the reduction was similar across the Aβ_1-37, Aβ_1-38, and Aβ_1-42 fragments in both atabecestat dose groups, consistent with Aβ_1-40. CSF amyloid precursor protein fragment (sAPPβ) levels declined from baseline, regardless of patient population, whereas CSF sAPPα levels increased compared with placebo. There were no relevant changes in either CSF total tau or phosphorylated tau 181P over a 4-week treatment period.

CONCLUSIONS

JNJ-54861911 at 10 and 50 mg daily doses after 4 weeks resulted in mean CSF Aβ_1-40 reductions of 67% and up to 90% in both Caucasian and Japanese patients with early stage AD, confirming results in healthy elderly adults.

TRIAL REGISTRATION

ALZ1005: ClinicalTrials.gov, NCT01978548. Registered on 7 November 2013. ALZ1008: ClinicalTrials.gov, NCT02360657. Registered on 10 February 2015.

Maintenance dose conversion between oral risperidone and paliperidone palmitate 1 month: Practical guidance based on pharmacokinetic simulations

AIM

We assessed the dosage strengths of paliperidone palmitate 1-month (PP1M) long-acting injectable resulting in similar steady-state (SS) exposures to the dosage strengths of oral risperidone using pharmacokinetic (PK) simulations.

METHODS

Population PK simulations of SS PK were performed using the PK models of oral risperidone and PP1M. The concentrations of active moiety (risperidone + paliperidone) from risperidone were compared to paliperidone concentrations resulting from PP1M administration. Similarity was assessed via graphical evaluation of median and 90% prediction intervals of SS PK profiles over 28 days.

RESULTS

Oral risperidone doses of 1, 2, 3, 4, and 6 mg/d are expected to result in similar SS PK as PP1M doses of 25, 50, 75, 100, and 150 mg eq. (which correspond to 39, 78, 117, 156, and 234 mg of paliperidone palmitate) respectively (ie 25-fold dose conversion factor from oral risperidone to PP1M).

CONCLUSIONS

This study provides clinicians with a practical guidance to establish suitable maintenance dose levels of PP1M and oral risperidone when transitioning patients from one formulation to another.

Evaluating Potential QT Effects of JNJ-54861911, a BACE Inhibitor in Single- and Multiple-Ascending Dose Studies, and a Thorough QT Trial With Additional Retrospective Confirmation, Using Concentration-QTc Analysis

Nonclinical assays with JNJ-54861911, a β-secretase 1 inhibitor have indicated that at high concentrations, it may delay cardiac repolarization. A 4-way crossover thorough QT (TQT) study was performed in 64 healthy subjects with 50 and 150 mg JNJ-54861911 once daily for 7 days, placebo, and 400 mg moxifloxacin. Retrospective high-precision QT (HPQT) analysis was performed on serial elecrocardiograms extracted from first-in-human single-ascending dose (SAD) and multiple-ascending dose (MAD) studies to evaluate if early studies could detect and predict QT effect. In the TQT study, a high therapeutic 50 mg dose did not cause QT prolongation, and an effect >10 milliseconds could be excluded at all postdose timepoints. QT prolongation with peak effect on placebo-corrected change from baseline QTcF of 15.5 milliseconds (90%CI, 12.9-18.1 milliseconds) was observed following a supratherapeutic dose (150 mg). No clinically relevant QT changes were observed in earlier studies. However, with SAD/MAD findings by HPQT, the slope of the exposure-response (ER) relationship in the SAD study (doses up to 150 mg) was similar to the TQT study slope, and the estimated QT effect was comparable at high plasma levels. In the MAD study, doses up to 90 mg once daily for 7 days resulted in JNJ-54861911 peak plasma concentrations (C_max ) comparable to those in the SAD study (∼750 ng/mL), but ER by HPQT failed to detect a QT effect and resulted in negative estimations. Adding a higher dose cohort (150 mg; C_max , 1125 ng/mL) demonstrated a QT effect, with a slightly lower ER slope than the TQT study. JNJ-54861911 (up to 50 mg) did not cause QT prolongation at clinically relevant plasma concentrations in any studies. Provided sufficiently high plasma concentrations were captured, mild QT prolongation observed postdose with a supratherapeutic dose could be detected (TQT study) and estimated in SAD/MAD studies. Based on population pharmacokinetic modeling and simulation, 5 and 25 mg doses are currently considered for further phase 3 studies and are expected not to cause any relevant QT prolongation.

Dosing and Switching Strategies for Paliperidone Palmitate 3-Month Formulation in Patients with Schizophrenia Based on Population Pharmacokinetic Modeling and Simulation, and Clinical Trial Data

Paliperidone palmitate 3-month formulation (PP3M), a long-acting injectable atypical antipsychotic, was recently approved in the US and Europe for the treatment of schizophrenia in adult patients who have already been treated with paliperidone palmitate 1-month formulation (PP1M) for ≥4 months. This article reviews the pharmacokinetic rationale for the approved dosing regimens for PP3M, dosing windows, management of missed doses and treatment discontinuation, switching to other formulations, and dosing in special populations. Approved PP3M dosing regimens are based on the comparisons of simulations with predefined dosing regimens using paliperidone palmitate and oral paliperidone extended release (ER) population pharmacokinetic models (one-compartment model with two saturable absorption processes for PP3M; one-compartment model with parallel zero- and first-order absorption for PP1M; two-compartment model with sequential zero- and first-order absorption for ER) versus clinical trial data. Covariates were obtained by resampling subject covariates from the pharmacokinetics database for PP1M and PP3M. Simulation scenarios with varying doses and covariate values were generated. The population median and 90% prediction interval of the simulated concentration-time profiles were plotted for simulation outcomes evaluation. Simulations described in this paper provide (a) simulated plasma exposures for switching from PP1M to PP3M, (b) support for a once-every-3-months injection cycle, (c) information on dosing windows and managing missed doses of PP3M, (d) important guidance on PP3M dosing in special patient populations, and (e) key PP3M pharmacokinetic exposure metrics based on the population pharmacokinetic PP3M model. Population pharmacokinetics provided practical guidance to establish dosing regimens for PP3M.

Profiling the dynamics of CSF and plasma Aβ reduction after treatment with JNJ-54861911, a potent oral BACE inhibitor

OBJECTIVES

Safety, tolerability, pharmacokinetics, and pharmacodynamics of a novel β-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitor, JNJ-54861911, were assessed after single and multiple dosing in healthy participants.

METHODS

Two randomized, placebo-controlled, double-blind studies were performed using single and multiple ascending JNJ-54861911 doses (up to 14 days) in young and elderly healthy participants. Regular blood samples and frequent CSF samples, up to 36 hours after last dose, were collected to assess the pharmacokinetic and pharmacodynamic (Aβ, sAPPα,β,total levels) profiles of JNJ-54861911.

RESULTS

JNJ-54861911 was well-tolerated, adverse events were uncommon and unrelated to JNJ-54861911. JNJ-54861911 showed dose-proportional CSF and plasma pharmacokinetic profiles. Plasma- and CSF-Aβ and CSF-sAPPβ were reduced in a dose-dependent manner. Aβ reductions (up to 95%) outlasted exposure to JNJ-54861911. APOE ε4 carrier status and baseline Aβ levels did not influence Aβ/sAPPβ reductions.

CONCLUSION

JNJ-54861911, a potent brain-penetrant BACE1 inhibitor, achieved high and stable Aβ reductions after single and multiple dosing in healthy participants.

Prospective dose selection and acceleration of paliperidone palmitate 3-month formulation development using a pharmacometric bridging strategy

AIMS

To prospectively select the dose of the paliperidone palmitate 3-month (PP3M) formulation, using a pharmacometric bridging strategy based on the paliperidone palmitate 1-month (PP1M) formulation previously approved for schizophrenia treatment.

METHODS

Pharmacokinetic (PK) data from a 6-month interim analysis of a single dose PP3M Phase I clinical trial was integrated with a previously developed PP1M population-PK model. The model was updated to incorporate formulation as a covariate on absorption parameters and to explore the most critical design element of the Phase III study: the PP1M-to-PP3M dose multiplier for patients switching formulations. Plasma paliperidone concentrations were measured at predetermined intervals during Phase III, enabling comparison of the multiple-dose PK between PP1M and PP3M. Exposure matching was assessed graphically to determine whether paliperidone plasma concentrations from the two formulations overlapped.

RESULTS

Prospective steady-state PK simulations revealed that a 3.5 multiple of the PP1M dose would yield a corresponding PP3M dose with comparable exposure. The prospective pharmacometric simulation and observed Phase III PK data agreed closely. Phase III results confirmed the hypothesis that efficacy of PP3M was noninferior to that of PP1M. The similarity in exposures between the two formulations was likely a key determinant of the equivalent efficacy between the two products observed in the Phase III study.

CONCLUSIONS

Successful prospective PP3M Phase III clinical trial dose selection was achieved through the use of pharmacometric bridging, without conducting a Phase II study and using only limited Phase I data for PP3M. We estimate that this strategy reduced development time by 3-5 years and may be applicable to other drug development projects.

Alzheimer's disease assessment scale-cognitive 11-item progression model in mild-to-moderate Alzheimer's disease trials of bapineuzumab

Introduction

The objective of this study was to estimate longitudinal changes in disease progression (measured by Alzheimer's disease assessment scale-cognitive 11-item [ADAS-cog/11] scale) after bapineuzumab treatment and to identify covariates (demographics or baseline characteristics) contributing to the variability in disease progression rate and baseline disease status.

Methods

A population-based disease progression model was developed using pooled placebo and bapineuzumab data from two phase-3 studies in APOE ε4 noncarrier and carrier Alzheimer's disease (AD) patients.

Results

A beta regression model with the Richard's function as the structural component best described ADAS-cog/11 disease progression for mild-to-moderate AD population. This analysis confirmed no effect of bapineuzumab exposure on ADAS-cog/11 progression rate, consistent with the lack of clinical efficacy observed in the statistical analysis of ADAS-cog/11 data in both studies. Assessment of covariates affecting baseline severity revealed that men had a 6% lower baseline ADAS-cog/11 score than women; patients who took two AD concomitant medications had a 19% higher (worse) baseline score; APOE ε4 noncarriers had a 5% lower baseline score; and patients who had AD for a longer duration had a higher baseline score. Furthermore, shorter AD duration, younger age, APOE ε4 carrier status, and use of two AD concomitant medications were associated with faster disease progression rates. Patients who had an ADAS-cog/11 score progression rate that was not statistically significantly different from 0 typically took no AD concomitant medications.

Discussion

The beta regression model is a sensible modeling approach to characterize cognitive decline in AD patients. The influence of bapineuzumab exposure on disease progression measured by ADAS-cog/11 was not significant.

Trial Registration

ClinicalTrials.gov identifier: NCT00575055 and NCT00574132.

Alzheimer's disease progression model using disability assessment for dementia scores from bapineuzumab trials

Objective

Disability assessment for dementia (DAD) measurements from two phase-3 studies of bapineuzumab in APOE ε4 noncarrier and carrier Alzheimer's disease (AD) patients were integrated to develop a disease progression model.

Methods

We evaluated longitudinal changes in DAD scores, baseline factors affecting disease progression, and bapineuzumab effect on disease progression.

Results

A beta regression model best described DAD disease progression. The estimated treatment effect of bapineuzumab was not significant, consistent with lack of clinical efficacy observed in the primary analysis. The model suggested that progression of DAD tended to decrease with increase in bapineuzumab exposure. The exposure-response relationship was similar regardless of APOE ε4 status but more pronounced in patients with mild AD. Baseline disease status, age, memantine use, and years since onset (YSO) had significant effects on baseline DAD scores. AD concomitant medication use, baseline disease status, and YSO had significant effects on disease progression rate, measured by DAD score.

Conclusions

The beta regression model is a sensible modeling approach to characterize functional decline in AD patients. This analysis suggested a possible effect of bapineuzumab exposure on DAD progression. Further evaluation may be warranted in future studies.

Trial Registration

ClinicalTrials.gov identifier: NCT00575055 and NCT00574132.

Population modelling of patient responses in antidepressant studies: a stochastic approach

This paper addresses the problem of modelling longitudinal data describing patients' responses in clinical trials. In particular, a systematic approach relying on a system theoretic paradigm is proposed to deal with contexts where limited physiopathological knowledge is available on disease, drug response, and patients' characteristics. The model relies on the notion of patient's health state which summarizes the patient's condition. In order to cope with the limited number of clinical data usually available, the paper considers a very parsimonious realization where the two state variables are the clinical endpoint and its derivative. Within a population framework, the individual response is modelled as the sum of an individual shift and the average response of subjects belonging to the same study, both described as Markovian processes and identified by empirical Bayes techniques. The proposed approach is validated with experimental data from a Phase II, flexible-dose, depression trial. The dose changes due to the flexible-dose scheme are handled as perturbations on the state. The connection between inter-individual variability and model stability is evaluated showing that the introduction of stable poles helps to describe populations whose range of individual responses does not diverge with time. In this way, good individual fittings and visual predictive checks were obtained for the clinical data. The proposed analysis provides a systematic approach to semi-mechanistic modelling when a precise knowledge of the physiological mechanisms of the disease is incomplete or missing.

Continuous-time Markov modelling of flexible-dose depression trials

The aim of this paper is to provide a systematic methodology for modelling longitudinal data to be used in contexts of limited or even absent knowledge of the physiological mechanism underlying the disease time course. Adopting a system-theoretic paradigm, a population response model is developed where the clinical endpoint is described as a function of the patient's health state. In particular, a continuous-time stochastic approach is proposed where the clinical score and its time-derivative summarize the patient's health state affected by a random term accounting for exogenous unpredictable factors. The proposed approach is validated on experimental data from the placebo and drug arms of a Phase II depression trial. Since some subjects in the trial may undergo changes in their treatment dose due to the flexible dosing scheme, dose escalations are modelled as instantaneous perturbations on the state. In its simplest form--an integrated Wiener process--was able to correctly capture the individual responses in both treatment arms. However, a better description of inter-individual variability was obtained by means of a stable Markovian model. Parameter estimation has been carried out according to the empirical Bayes method.

Population model of longitudinal FEV1 data in asthmatics: meta-analysis and predictability of placebo response

Asthma is an obstructive lung disease where the mechanism of disease progression is not fully understood hence motivating the use of empirical models to describe the evolution of the patient's health state. With reference to placebo response, measured in terms of FEV1 (Forced Expiratory Volume in 1 s), a range of empirical models taken from the literature were compared at a single trial level. In particular, eleven GSK trials lasting 12 weeks in mild-to-moderate asthma were used for the modelling of longitudinal placebo responses. Then, the chosen exponential model was used to carry out an individual participant data meta-analysis on eleven trials. A covariate analysis was also performed to find relevant covariates in asthma to be accounted for in the meta-analysis model. Age, gender, and height were found statistically significant (e.g. the taller the patients the higher the FEV1, the older the patients the lower the FEV1, and females have lower FEV1). By truncating each trial at week 4, the predictive properties of the meta-analysis model were also investigated, showing its ability to predict long-term FEV1 response from truncated trials. Summarizing, the study suggests that: (i) the exponential model effectively describes the placebo response; (ii) the meta-analysis approach may prove helpful to simulate new trials as well as to reduce trial duration in view of its predictive properties; (iii) the inclusion of available covariates within the meta-analysis model provides a reduction of the inter-individual variability.

A PCA approach to population analysis: with application to a Phase II depression trial

For psychiatric diseases, established mechanistic models are lacking and alternative empirical mathematical structures are usually explored by a trial-and-error procedure. To address this problem, one of the most promising approaches is an automated model-free technique that extracts the model structure directly from the statistical properties of the data. In this paper, a linear-in-parameter modelling approach is developed based on principal component analysis (PCA). The model complexity, i.e. the number of components entering the PCA-based model, is selected by either cross-validation or Mallows' Cp criterion. This new approach has been validated on both simulated and clinical data taken from a Phase II depression trial. Simulated datasets are generated through three parametric models: Weibull, Inverse Bateman and Weibull-and-Linear. In particular, concerning simulated datasets, it is found that the PCA approach compares very favourably with some of the popular parametric models used for analyzing data collected during psychiatric trials. Furthermore, the proposed method performs well on the experimental data. This approach can be useful whenever a mechanistic modelling procedure cannot be pursued. Moreover, it could support subsequent semi-mechanistic model building.

Bayesian population approaches to the analysis of dose escalation studies

In dose escalation studies cohorts of subjects are given increasing doses of a candidate drug to assess safety and tolerability, pharmacokinetics and pharmacological response. The escalation is carried on until a predefined stopping limit is achieved, often identified by a pharmacokinetic endpoint such as peak plasma concentration or area under the plasma concentration-time profile. In the present work, the application of Bayesian methodologies to Phase I dose escalation studies is explored. A Bayesian population model is devised, which provides predictions of dose-response and dose-risk curves, both for individuals already enrolled in the trial and for a new, previously untested subject. Empirical and fully Bayesian estimation algorithms are worked out. Such methods provide equivalent performances on both experimental and simulated datasets. With respect to previous work, it is quantitatively proven not only that a more general and flexible model is identifiable, but also that such flexibility is needed in real scenarios.

Stochastic model search with binary outcomes for genome-wide association studies

Objective

The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses.

Materials and methods

Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor.

Results

BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes.

Discussion

BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques.

Conclusion

The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Modelling of the outcome of non-inferiority trials by integration of historical data

The approval and differentiation of new compounds in clinical development often demands non-inferiority trials, in which the test drug is compared against a reference treatment. However, non-inferiority trials impose major operational burden with serious ethical and scientific implications for the development of new medicines. Traditional approaches make limited use of historical information on placebo and neglect inter-trial variability, relying on the constancy assumption that the control-to-placebo effect size is maintained across trials. We propose a model-based approach that overcomes such limitations and may be used as a tool to explore differentiation during clinical development. Parameter distributions are introduced which reflect the heterogeneity of trials. The method is illustrated using data from impetigo trials. Based on simulation scenarios, this Bayesian technique yields a definitive, consistent increase in the statistical power over two accepted statistical methods, allowing lower sample size requirements for the assessment of non-inferiority.

Bayesian population modeling of phase I dose escalation studies: Gaussian process versus parametric approaches

The early stages of the drug development process are often characterized by a limited number of subjects participating the study and a limited number of measurements per individual that can be collected, mainly due to technical, ethical, and cost reasons. The so-called dose escalation studies, performed during phase I, usually involve about 40 subjects or less, and feature observations at no more than three (rarely four or five) dose levels-per-subject. Depending on the complexity of the underlying pharmacokinetics, simple linear models or nonlinear ones (e.g., power, E(max) models) may be appropriate to describe the relationship between the metrics of systemic exposure to the drug (C(max), AUC) and the administered dose. However, in such data-poor scenarios, formulating models based on parametric descriptions is generally hard, and may easily result in model misspecification. Hence, nonparametric or "model-free" solutions, borrowed from the machine learning field, are deemed appealing. We resort to Gaussian process theory to work out Bayesian posterior expectations of a population (a.k.a mixed-effects) regression problem, namely Population Smoothing Splines (PSS). We show that in seven experimental dose escalation studies, Population Smoothing Splines improve on three widely used parametric population methods. Superiority of the model-free technique is confirmed by a simulated benchmark: Population Smoothing Splines compare very favorably even with the true parametric model structure underlying the simulated data.