The Many Flavors of Model-Based Meta-Analysis: Part I-Introduction and Landmark Data

New Horizons of Model Informed Drug Development in Rare Diseases Drug Development

Model-informed approaches provide a quantitative framework to integrate all available nonclinical and clinical data, thus furnishing a totality of evidence approach to drug development and regulatory evaluation. Maximizing the use of all available data and information about the drug enables a more robust characterization of the risk-benefit profile and reduces uncertainty in both technical and regulatory success. This offers the potential to transform rare diseases drug development, where conducting large well-controlled clinical trials is impractical and/or unethical due to a small patient population, a significant portion of which could be children. Additionally, the totality of evidence generated by model-informed approaches can provide confirmatory evidence for regulatory approval without the need for additional clinical data. In the article, applications of novel quantitative approaches such as quantitative systems pharmacology, disease progression modeling, artificial intelligence, machine learning, modeling of real-world data using model-based meta-analysis and strategies such as external control and patient-reported outcomes as well as clinical trial simulations to optimize trials and sample collection are discussed. Specific case studies of these modeling approaches in rare diseases are provided to showcase applications in drug development and regulatory review. Finally, perspectives are shared on the future state of these modeling approaches in rare diseases drug development along with challenges and opportunities for incorporating such tools in the rational development of drug products.

Efficacy and dose-response relationships of antidepressants in the acute treatment of major depressive disorders: a systematic review and network meta-analysis

BACKGROUND

The optimal antidepressant dosages remain controversial. This study aimed to analyze the efficacy of antidepressants and characterize their dose-response relationships in the treatments of major depressive disorders (MDD).

METHODS

We searched multiple databases, including the Embase, Cochrane Central Register of Controlled Trials, PubMed, and Web of Science, for the studies that were conducted between January 8, 2016, and April 30, 2023. The studies are double-blinded, randomized controlled trials (RCTs) involving the adults (≥18 years) with MDD. The primary outcomes were efficacy of antidepressant and the dose-response relationships. A frequentist network meta-analysis was conducted, treating participants with various dosages of the same antidepressant as a single therapy. We also implemented the model-based meta-analysis (MBMA) using a Bayesian method to explore the dose-response relationships.

RESULTS

The network meta-analysis comprised 135,180 participants from 602 studies. All the antidepressants were more effective than the placebo; toludesvenlafaxine had the highest odds ratio (OR) of 4.52 (95% confidence interval [CI]: 2.65-7.72), and reboxetine had the lowest OR of 1.34 (95%CI: 1.14-1.57). Moreover, amitriptyline, clomipramine, and reboxetine showed a linear increase in effect size from low to high doses. The effect size of toludesvenlafaxine increased significantly up to 80 mg/day and subsequently maintained the maximal dose up to 160 mg/day while the predictive curves of nefazodone were fairly flat in different dosages.

CONCLUSIONS

Although most antidepressants were more efficacious than placebo in treating MDD, no consistent dose-response relationship between any antidepressants was observed. For most antidepressants, the maximum efficacy was achieved at lower or middle prescribed doses, rather than at the upper limit.

Quantitative evaluation of the time-course and efficacy of targeted agents for ulcerative colitis

Background

Targeted agents are widely utilized in the treatment of ulcerative colitis (UC). Hence, a comprehensive understanding of comparative drug efficacy in UC is of great importance for drug development and clinical practice. Our objective was the quantitative evaluation of the comparative efficacy of targeted agents for UC.

Methods

Three mathematical models were developed based on data from randomized controlled trials in patients with moderate-to-severe UC to describe the time-course and dose-response of efficacy defined as clinical remission, clinical response, and endoscopic improvement, as well as the placebo effect. The covariate effects were further evaluated. Model simulation was performed in a hypothetical population to compare the efficacies across different drugs.

Results

The analysis dataset was composed of data from 35 trials of 12 drugs in UC. Time-response relationships were evaluated that indicated a gradual onset of drug efficacy in adalimumab, ozanimod, and Janus kinase (JAK) inhibitors. The dose-response relationships were estimated for each drug respectively. Patient age, disease duration, baseline weight, prior tumor necrosis factor (TNF) inhibitor exposure, and current treatment with corticosteroid showed an impact on efficacy, suggesting that younger patients with shorter UC duration without prior anti-TNF treatment and current corticosteroids therapy tend to display greater treatment effects.

Conclusion

This study developed three longitudinal models for UC to quantitatively describe the efficacy of targeted agents, as well as the influencing factors of efficacy. Infliximab and upadacitinib were determined to be the most effective biological and small targeted molecules, respectively. These findings may provide valuable implications for guiding future decision-making in clinical practice and drug development for UC.

Modeling an evaluation of the efficacy of the novel neuroanalgesic drug mirogabalin for diabetic peripheral neuropathic pain and postherpetic neuralgia therapy

Diabetic peripheral neuropathic pain (DPNP) and postherpetic neuralgia (PHN) are challenging and often intractable complex medical conditions, with a substantial impact on the quality of life. Mirogabalin, a novel voltage-gated Ca2+ channel α2δ ligand, was approved for the indication of DPNP and PHN. However, the time course of effects has not yet been clarified.We aimed to establish pharmacodynamic and placebo effect models of mirogabalin and pregabalin in DPNP and PHN, and to quantitatively compare the efficacy characteristics (maximum efficacy, onset time, and other pharmacodynamic parameters) and safety of mirogabalin and pregabalin. Public databases were comprehensively searched for randomized placebo-controlled clinical trials. A model-based meta-analysis (MBMA) was developed to describe the time course of drug efficacy and placebo effects. Adverse events were compared using a fixed-effects meta-analysis. Sixteen studies including 5,147 participants were eligible for this study. The placebo effect was relatively high and gradually increased with time, and it required at least eight weeks to reach a plateau. The pharmacodynamic model revealed that the maximum pure efficacy for mirogabalin and pregabalin was approximately -7.85 % and -8.86 %, respectively; the efficacy of mirogabalin to relieve DPNP and PHN was not superior to that of pregabalin, and both drugs had similar safety. While the rate constant of the onset rate of pregabalin was approximately thrice as high as that of mirogabalin. In addition, the baseline level of pain was an important factor affecting pregabalin efficacy. These findings are helpful in evaluating the clinical extension value of mirogabalin. They suggest that the high placebo effect and the baseline level of pain should be considered when grouping patients in future research and development of voltage-gated Ca2+ channel neuroanalgesic.

Dose-response relationships of intravenous and perineural dexamethasone as adjuvants to peripheral nerve blocks: a systematic review and model-based network meta-analysis

BACKGROUND

Superiority of perineural over intravenous dexamethasone at extending nerve block analgesia has been suggested but without considering the dose-response relationships for each route of administration.

METHODS

Randomised control studies that evaluated intravenous or perineural dexamethasone as an adjuvant to unilateral peripheral nerve blocks in adults were searched up to October 2023 in MEDLINE, Central, Google Scholar, and reference lists of previous systematic reviews. The Cochrane Risk-of-Bias tool was used. A maximum effect (Emax) model-based network meta-analysis was undertaken to evaluate the dose-response relationships of dexamethasone.

RESULTS

A total of 118 studies were selected (9284 patients; 35 with intravenous dexamethasone; 106 with perineural dexamethasone; dose range 1-16 mg). Studies with unclear or high risk of bias overestimated the effect of dexamethasone. Bias-corrected estimates indicated a maximum fold increase in analgesia duration of 1.7 (95% credible interval (CrI) 1.4-1.9) with dexamethasone, with no difference between perineural and intravenous routes. Trial simulations indicated that 4 mg of perineural dexamethasone increased the mean duration of analgesia for long-acting local anaesthetics from 11.1 h (95% CrI 9.4-13.1) to 16.5 h (95% CrI 14.0-19.3) and halved the rate of postoperative nausea and vomiting. A similar magnitude of effect was observed with 8 mg of intravenous dexamethasone.

CONCLUSIONS

Used as an adjuvant for peripheral nerve block, intravenous dexamethasone can be as effective as perineural dexamethasone in prolonging analgesic duration, but is less potent, hence requiring higher doses. The evidence is limited because of the observational nature of the dose-response relationships and the quality of the included studies.

SYSTEMATIC REVIEW PROTOCOL

PROSPERO CRD42020141689.

Longitudinal Meta-Analysis of Historical Parkinson's Disease Trials to Inform Future Trial Design

BACKGROUND

The outcome of clinical trials in neurodegeneration can be highly uncertain due to the presence of a strong placebo effect.

OBJECTIVES

To develop a longitudinal model that can enhance the success of future Parkinson's disease trials by quantifying trial-to-trial variations in placebo and active treatment response.

METHODS

A longitudinal model-based meta-analysis was conducted on the total score of Unified Parkinson's Disease Rating Scale (UPDRS) Parts 1, 2, and 3. The analysis included aggregate data from 66 arms (observational [4], placebo [28], or investigational-drug-treated [34]) from 4 observational studies and 17 interventional trials. Inter-study variabilities in key parameters were estimated. Residual variability was weighted by the size of study arms.

RESULTS

The baseline total UPDRS was estimated to average at 24.5 points. Disease score was estimated to worsen by 3.90 points/year for the duration of the treatments; whilst notably, arms with a lower baseline progressed faster. The model captured the transient nature of the placebo response and sustained symptomatic drug effect. Both placebo and drug effects peaked within 2 months; although, 1 year was needed to observe the full treatment difference. Across these studies, the progression rate varied by 59.4%, the half-life for offset of placebo response varied by 79.4%, and the amplitude for drug effect varied by 105.3%.

CONCLUSION

The longitudinal model-based meta-analysis describes UPDRS progression rate, captures the dynamics of the placebo response, quantifies the effect size of the available therapies, and sets the expectation of uncertainty for future trials. The findings provide informative priors to enhance the rigor and success of future trials of promising agents, including potential disease modifiers. © 2023 GSK. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Optimization of secukinumab dose regimens in patients with moderate-to-severe plaque psoriasis via exposure-response modeling

BACKGROUND

Further dose optimization is required for patients with moderate-to-severe plaque psoriasis who do not benefit from the approved secukinumab dose regimen. This study aimed to develop an exposure-response model for secukinumab to recommend dose regimens for patients of different body weights.

METHODS

We searched the PubMed and Cochrane Library databases for randomized controlled trials using PASI 75 and PASI 90 response rates as primary outcomes. A model-based meta-analysis was developed to quantitatively analyze the distribution of six secukinumab dose regimens in patients weighing 50-120 kg.

RESULTS

Sixteen trials involving 6,197 subjects were included in the analysis. The established model accurately described the time-course characteristics of PASI 75 and PASI 90 response rates over 52 weeks. Simulations indicated that maintenance doses could be reduced to 150 mg every 4 weeks and to 150 mg every 3 weeks for patients weighing 50 and 60 kg, respectively. In contrast, maintenance doses of 300 mg every 3 weeks should be selected for patients weighing 120 kg. Patients weighing 70-110 kg remained on approved maintenance doses of 300 mg every 4 weeks.

CONCLUSIONS

Based on patient body weights, the exposure-response model recommends efficacious and economical dose regimens for patients with moderate-to-severe plaque psoriasis.

BAYESIAN HIERARCHICAL RANDOM-EFFECTS META-ANALYSIS AND DESIGN OF PHASE I CLINICAL TRIALS

We propose a curve-free random-effects meta-analysis approach to combining data from multiple phase I clinical trials to identify an optimal dose. Our method accounts for between-study heterogeneity that may stem from different study designs, patient populations, or tumor types. We also develop a meta-analytic-predictive (MAP) method based on a power prior that incorporates data from multiple historical studies into the design and conduct of a new phase I trial. Performances of the proposed methods for data analysis and trial design are evaluated by extensive simulation studies. The proposed random-effects meta-analysis method provides more reliable dose selection than comparators that rely on parametric assumptions. The MAP-based dose-finding designs are generally more efficient than those that do not borrow information, especially when the current and historical studies are similar. The proposed methodologies are illustrated by a meta-analysis of five historical phase I studies of Sorafenib, and design of a new phase I trial.

Applications of Model-Based Meta-Analysis in Drug Development

Model-based meta-analysis (MBMA) is a quantitative approach that leverages published summary data along with internal data and can be applied to inform key drug development decisions, including the benefit-risk assessment of a treatment under investigation. These risk-benefit assessments may involve determining an optimal dose compared against historic external comparators of a particular disease indication. MBMA can provide a flexible framework for interpreting aggregated data from historic reference studies and therefore should be a standard tool for the model-informed drug development (MIDD) framework.In addition to pairwise and network meta-analyses, MBMA provides further contributions in the quantitative approaches with its ability to incorporate longitudinal data and the pharmacologic concept of dose-response relationship, as well as to combine individual- and summary-level data and routinely incorporate covariates in the analysis.A common application of MBMA is the selection of optimal dose and dosing regimen of the internal investigational molecule to evaluate external benchmarking and to support comparator selection. Two case studies provided examples in applications of MBMA in biologics (durvalumab + tremelimumab for safety) and small molecule (fenebrutinib for efficacy) to support drug development decision-making in two different but well-studied disease areas, i.e., oncology and rheumatoid arthritis, respectively.Important to the future directions of MBMA include additional recognition and engagement from drug development stakeholders for the MBMA approach, stronger collaboration between pharmacometrics and statistics, expanded data access, and the use of machine learning for database building. Timely, cost-effective, and successful application of MBMA should be part of providing an integrated view of MIDD.

Quantitative evaluation of drug efficacy in the treatment of myasthenia gravis

OBJECTIVES

This study aimed to quantitatively evaluate placebo effect and drug efficacy characteristics and identify associated factors that affect quantitative myasthenia gravis (MG) score (QMGs) and MG activities of daily living score (MG-ADLs) in patients with MG.

METHODS

Randomized placebo-controlled clinical trials were comprehensively searched in public databases (PubMed, EMBASE, and Cochrane Library databases).A model-based meta-analysis was developed to describe time-course about drug efficacy and placebo effect.

RESULTS

Twelve articles including 13 trials (673 participants) that were eligible for this study evaluated four immunosuppressants (tacrolimus, cyclosporine, prednisone, and mycophenolate mofetil) and five targeted therapy drugs (eculizumab, belimumab, zilucoplan, efgartigimod, and iscalimab). The pharmacodynamic model showed that eculizumab had the highest efficacy in reducing QMGs scores (3.66 points), and efgartigimod had the highest efficacy in reducing MG-ADLs scores (1.97 points). The placebo effect of QMGs and MG-ADLs increased apparently with time and reached 52% and 90% of their maximum effect in 12 weeks, respectively. In addition, this study found that the activities of daily living ability increased with the increase of the proportion of patients undergoing thymectomy.

CONCLUSION

This study analyzed the efficacy characteristics of nine drugs. The present findings provide necessary quantitative information for drug development of MG.

Development and Application of the Placebo Response Model in Clinical Trials for Primary Sjögren's Syndrome

This study aimed to develop a placebo response model for pharmaceutical clinical trials of primary Sjogren's syndrome,and to quantitatively analyze the distribution and related factors influencing the placebo response to further optimize the design of clinical trials and evaluate the results of single-arm clinical trials. Public databases, including PubMed, Embase, and Cochrane Library were searched for reports on randomized placebo-controlled trials for Sjögren's syndrome which used the change from baseline in ESSDAI score as the primary outcome. The model-based meta-analysis method was used to evaluate the time course and the related influencing factors of the placebo response for ESSDAI in such clinical trials. A virtual placebo control group was constructed based on the final placebo response model to determine the treatment efficacy of belimumab and cyclosporine A for primary Sjögren's syndrome in a single-arm study. A total of 12 studies involving 450 subjects were included in the analysis. The established model described the time-course characteristics of the changes in ESSDAI score from the baseline in the 48 weeks placebo group. We found that the onset time of placebo response was approximately 12 weeks, and its efficacy plateaued at 48 weeks. The baseline ESSDAI score had a significant effect on the maximum value of the placebo response; the maximum value of the placebo response decreased by 0.552 for every 1 score rise in the baseline ESSDAI score. The efficacy of belimumab and cyclosporine A in the single-arm trial was comparable to that of the placebo response at the same baseline; no significant therapeutic advantage was observed. The placebo response model established in this study could provide a basis for designing clinical trials for primary Sjogren's syndrome in the future. It may also provide a reliable external efficacy control standard for single-arm clinical trials.

Factors affecting the efficacy and safety of docetaxel combined with platinum in the treatment of advanced non-small cell lung cancer

BACKGROUND

This study aimed to quantitatively evaluate factors influencing the efficacy and safety of the docetaxel-platinum regimen to provide reliable information for optimizing chemotherapy regimens.

RESEARCH DESIGN AND METHODS

A parametric survival function model was used to describe the time course of overall survival (OS) of patients with advanced non-small cell lung cancer (NSCLC) receiving a docetaxel-platinum regimen. A random-effects model in a single-arm meta-analysis was used to analyze the objective response rate and grade 3-4 adverse event rates based on various docetaxel-platinum regimens.

RESULTS

The model revealed that the risk of death in East Asians was approximately 1.5-fold higher than that in non-East Asians, with a median OS of 13.7 (95% confidence interval [CI]: 12.8-14.7) months and 9.3 (95% CI: 7.7-11.1) months, respectively. No significant impact of different administration regimens on OS was found. However, when drug exposure increased, the incidence of grade 3-4 anemia or neutropenia significantly increased.

CONCLUSIONS

The docetaxel-platinum regimen has different efficacies in the treatment of advanced NSCLC between East Asian and non-East Asian populations. A better benefit-risk ratio can be obtained with a lower exposure regimen of docetaxel combined with platinum.

End-to-end application of model-informed drug development for ertugliflozin, a novel sodium-glucose cotransporter 2 inhibitor

Model-informed drug development (MIDD) is critical in all stages of the drug-development process and almost all regulatory submissions for new agents incorporate some form of modeling and simulation. This review describes the MIDD approaches used in the end-to-end development of ertugliflozin, a sodium-glucose cotransporter 2 inhibitor approved for the treatment of adults with type 2 diabetes mellitus. Approaches included (1) quantitative systems pharmacology modeling to predict dose-response relationships, (2) dose-response modeling and model-based meta-analysis for dose selection and efficacy comparisons, (3) population pharmacokinetics (PKs) modeling to characterize PKs and quantify population variability in PK parameters, (4) regression modeling to evaluate ertugliflozin dose-proportionality and the impact of uridine 5'-diphospho-glucuronosyltransferase (UGT) 1A9 genotype on ertugliflozin PKs, and (5) physiologically-based PK modeling to assess the risk of UGT-mediated drug-drug interactions. These end-to-end MIDD approaches for ertugliflozin facilitated decision making, resulted in time/cost savings, and supported registration and labeling.

A Systematic Review and Meta-Analysis on the Longitudinal Effects of Unilateral Knee Extension Exercise on Muscle Strength

The aim of the study was to investigate the time-dependent increase in the knee extensors' isometric strength as a response to voluntary, unilateral, isometric knee extension exercise (UIKEE). To do so, a systematic review was carried out to obtain data for a Bayesian longitudinal model-based meta-analysis (BLMBMA). For the systematic review, PubMed, Web of Science, SCOPUS, Chochrane Library were used as databases. The systematic review included only studies that reported on healthy, young individuals performing UIKEE. Studies utilizing a bilateral training protocol were excluded as the focus of this review lied on unilateral training. Out of the 3,870 studies, which were reviewed, 20 studies fulfilled the selected inclusion criteria. These 20 studies were included in the BLMBMA to investigate the time-dependent effects of UIKEE. If compared to the baseline strength of the trained limb, these data reveal that UKIEE can increase the isometric strength by up to 46%. A meta-analysis based on the last time-point of each available study was employed to support further investigations into UIKEE-induced strength increase. A sensitivity analysis showed that intensity of training (%MVC), fraction of male subjects and the average age of the subject had no significant influence on the strength gain. Convergence of BLMBMA revealed that the peak strength increase is reached after ~4 weeks of UIKEE training.

Comparative Efficacy of Drugs for the Treatment of Chronic Constipation: Quantitative Information for Medication Guidelines

BACKGROUND

Quantitative information is scarce with regard to guidelines for currently prescribed medications for constipation. Furthermore, these guidelines do not reflect the differences in the number of bowel movements caused by each drug.

GOALS

In this study, we used a model-based meta-analysis to quantitatively estimate the deviations from the baseline number of spontaneous bowel movements (SBMs) and complete spontaneous bowel movements (CSBMs) associated with pharmacotherapy for chronic constipation to bridge the knowledge gap in the guidelines for current medications.

STUDY

A comprehensive survey was conducted using literature databases. In this study, we also included randomized placebo-controlled trials on chronic constipation. Pharmacodynamic models were established to describe the time course of the numbers of SBMs and CSBMs produced by each drug.

RESULTS

Data from 20 studies (comprising 9998 participants and 8 drugs) were used to build this model. The results showed that bisacodyl had the greatest effect on increasing the frequency of bowel movements, whereas plecanatide yielded the lowest increase in the number of SBMs and CSBMs. After eliminating the placebo effect, the maximal increase in bowel movement frequency associated with bisacodyl was 6.8 for SBMs (95% confidence interval: 6.1-7.6) and 4.7 for CSBMs (95% confidence interval: 4.3-5.1) per week. These numbers are ∼4 times higher than the number of bowel movements produced by plecanatide. The change in the frequency of SBMs and CSBMs for other drugs, such as sodium picosulfate, velusetrag, linaclotide, elobixibat, lubiprostone, and prucalopride, was similar. The highest increases in the frequency of SBM and CSBM were 2.5 to 4 and 1 to 2.1 per week, respectively. Bisacodyl had the most noticeable loss of efficacy between week 1 and week 4; it reduced the frequencies of SBMs and CSBMs by 2.3 and 2.2, respectively. By contrast, the changes in the frequencies of SBMs and CSBMs were not as great with other drugs.

CONCLUSIONS

The data provided in this study may be a valuable supplement to the medication guidelines for the treatment of chronic constipation.

Time course and dose effect of metformin on weight in patients with different disease states

OBJECTIVES

The present study was to quantitate and compare the efficacy of metformin on weight in different disease states using model-based meta-analysis (MBMA).

METHODS

Randomized controlled trials (RCT) of metformin effects on weight in different disease states were collected by searching the public databases. The change rate of weight from baseline was selected as the efficacy indicator.

RESULTS

A total 21 RCTs containing 1885 patients including patients with type 2 diabetes mellitus, patients with antipsychotic induced weight gain, patients with obesity, were included into the present study. After deducting placebo effect, the maximal effect (E_max) of metformin on weight in patients with type 2 diabetes mellitus, patients with antipsychotic induced weight gain, patients with obesity were -6.86%, -8.82%, and -4.14%, respectively. The treatment duration to reach half of the maximal effect (ET₅₀) were 107, 45.5, and 15.1 weeks, respectively. Within the metformin dose range from 21 RCTs, no significant dose-response relationship was observed. However, the time-course relationship is obvious for efficacy of metformin on weight.

CONCLUSIONS

The present study firstly provided quantitative information for metformin effects on weight in different disease states, including patients with type 2 diabetes mellitus, patients with antipsychotic induced weight gain, patients with obesity.

Incorporating Pharmacometrics into Pharmacoeconomic Models: Applications from Drug Development

Pharmacometrics is the science of quantifying the relationship between the pharmacokinetics and pharmacodynamics of drugs in combination with disease models and trial information to aid in drug development and dosing optimization for clinical practice. Considering the variability in the dose-concentration-effect relationship of drugs, an opportunity exists in linking pharmacokinetic and pharmacodynamic model-based estimates with pharmacoeconomic models. This link may provide early estimates of the cost effectiveness of drug therapies, thus informing late-stage drug development, pricing, and reimbursement decisions. Published case studies have demonstrated how integrated pharmacokinetic-pharmacodynamic-pharmacoeconomic models can complement traditional pharmacoeconomic analyses by identifying the impact of specific patient sub-groups, dose, dosing schedules, and adherence on the cost effectiveness of drugs, thus providing a mechanistic basis to predict the economic value of new drugs. Greater collaboration between the pharmacoeconomics and pharmacometrics community can enable methodological improvements in pharmacokinetic-pharmacodynamic-pharmacoeconomic models to support drug development.

Analysis of time course and dose effect of tacrolimus on proteinuria in lupus nephritis patients

WHAT IS KNOWN AND OBJECTIVES

Tacrolimus is used to treat patients with lupus nephritis; however, its time course and dose effect on proteinuria in lupus nephritis patients remain unknown. The purpose of this study was to determine the time course and dose effect of tacrolimus on proteinuria in lupus nephritis patients via model-based meta-analysis (MBMA).

METHODS

PubMed, Web of Science, Cochrane Library and ClinicalTrials.gov databases were systematically searched for information on the efficacy of tacrolimus against proteinuria in lupus nephritis patients. Useful data were extracted to build a model for the population studied using a non-linear mixed-effect model (NONMEM). This model was applied to simulate time course of tacrolimus on proteinuria using Monte Carlo simulations.

RESULTS

Ten clinical studies that recruited 222 patients with lupus nephritis were included. Based on various diagnostic plots, we found that the established model described the observed data reasonably well. In addition, the typical E_max and ET₅₀ of tacrolimus for 24-hour proteinuria in lupus nephritis patients were -5.88 g and 0.37 months, respectively. The baseline value of 24-hour proteinuria affected E_max . No significant dose-response relationship was observed in the range of tacrolimus concentration used in the present study (3-10 ng/mL), indicating that the effect of tacrolimus on proteinuria depends on effective concentration range and not the dose. However, the time course relationship was obvious; the efficacy of tacrolimus increased over time, reaching a plateau (80% E_max ) at approximately 1.48 months from the beginning of treatment.

WHAT IS NEW AND CONCLUSION

When the concentration range of tacrolimus is maintained at 3-10 ng/mL, at least 1.48 months of treatment is required to achieve a better outcome with regard to proteinuria in lupus nephritis patients.

Study Design Characteristics and Pharmacological Mechanisms in International Clinical Trials Registry Platform: Registered Clinical Trials on Antiviral Drugs for COVID-19

OBJECTIVE

This study aimed to evaluate the pharmacological mechanisms of antiviral drugs against the novel coronavirus disease (COVID-19) and the study designs in clinical trials registered with the International Clinical Trials Registry Platform (ICTRP).

METHODS

Clinical trials involving antiviral drugs for treating COVID-19 were retrieved from the ICTRP database. For each trial, the study design, number of participants, primary endpoints, source register, antiviral mechanism, and results were evaluated.

RESULTS

On June 10, 2020, 145 eligible clinical trials were retrieved from the ICTRP, of which 99 (68.3%) were randomized trials, 109 (75.2%) were parallel assignment trials, 38 (26.2%) were double or single blinded, 130 (89.7%) involved two groups, and 75 (51.6%) included more than 100 participants; and clinical improvement or recovery and virus-negative conversion were the two most common endpoints, accounting for 40.7% and 18.6%, respectively. The drugs were divided according to the antiviral mechanism into HIV reverse transcriptase inhibitors, RNA-dependent RNA polymerase inhibitors, HIV protease inhibitors (PIs), hepatitis C virus NS3 PIs, and anti-influenza drugs.

CONCLUSION

The design characteristics of clinical trials of antiviral drugs for treating COVID-19 as well as the mechanism of action and antiviral efficacy of the drugs were evaluated in this study. The results of these trials could constitute a reference for future clinical trials to be executed on COVID-19 treatment and prevention.

The response-time relationship and covariate effects of acupuncture for chronic pain: A systematic review and model-based longitudinal meta-analysis

BACKGROUND AND OBJECTIVE

Critical clinical questions regarding how soon and how long the analgesic effect will be achieved by acupuncture, as well as who will be responsive to acupuncture, need further address. The aim of the study was to investigate the response-time relationship and covariate effects of acupuncture.

DATABASES AND DATA TREATMENT

PubMed and EMBASE were searched up to December 2018 for randomized controlled trials that involved sham acupuncture, true acupuncture and conventional therapy. We used a model-based longitudinal meta-analysis to characterize the response-time profile of these treatments.

RESULTS

Seventy-seven randomized clinical trials involved chronic shoulder, neck, knee and low back pain were included. The response-time analysis suggested that the treatment duration of acupuncture will be 5 weeks or more to achieve 80% of maximum analgesic effect. Moreover a lower baseline pain intensity and the location of low back pain resulted in a lower pain relief of acupuncture intervention. The absolute maximum analgesic effects of sham acupuncture and conventional therapy were 22.6 and 15.8 points at a 0-100 NRS scale. The absolute effect of true acupuncture was 26.1 points for low back pain (relative effect of 3.5 and 9.4 points to sham and conventional therapy), 34.9 points for other pain body locations (relative effect of 12.3 and 19.1 points to sham and conventional therapy), in patients with a baseline pain intensity of 60 points.

CONCLUSION

The treatment duration of acupuncture will not be less than 5 weeks to achieve 80% maximum analgesic effect. Higher analgesic effect was related to higher baseline pain intensity and pain location of neck, shoulder and knee.

SIGNIFICANCE

Our systematic review and meta-analysis provides the clear evidence for the treatment duration and significant related covariates of acupuncture intervention for chronic pain. These results provide useful suggestion for acupuncture intervention in clinical pain management.

Population Pharmacokinetics of Sertraline in Healthy Subjects: a Model-Based Meta-analysis

Sertraline pharmacokinetics is poorly understood and highly variable due to large between-subject variability with inconsistent reports for oral bioavailability. The study objective was to characterize sertraline pharmacokinetics by developing and validating a sertraline population pharmacokinetic (PK) model in healthy subjects using published clinical PK data. We carried a systematic literature search in PubMed in October 2015 and identified 27 pharmacokinetic studies of sertraline conducted in healthy adult subjects and reported in the English language. Sixty mean plasma concentration-time profiles made of 748 plasma concentrations following IV, single, and multiple oral doses ranging from 5 to 400 mg were extracted and analyzed for dose proportionality by a log-linear model and fitted to a 2-compartment pharmacokinetic model in NONMEM using a model-based meta-analysis (MBMA) approach. After a single oral dose, sertraline C_max and AUC_∞ increased with dose proportionally between 50 and 200 mg, and bioavailability increased nonlinearly with dose from 5 to 50 mg and plateaued afterwards while T_max and t_1/2 did not change with dose. Following multiple oral doses, C_max and AUC_∞ increased proportionally with dose across the entire dose range (5-200 mg) while bioavailability, T_max, and t_1/2 remained constant with dose. Sertraline absorption was time-dependent and best described by a sigmoidal E_max function of time after dose. Study findings indicate that sertraline PK is linear in healthy adult subjects at doses ≥ 50 mg, and exposures were nonlinear only after single oral doses < 50 mg likely due to reduced bioavailability.

Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach

AIMS

The objective of this study is to develop a generic model for tacrolimus pharmacokinetics modelling using a meta-analysis approach, that could serve as a first step towards a prediction tool to inform pharmacokinetics-based optimal dosing of tacrolimus in different populations and indications.

METHODS

A systematic literature review was performed and a meta-model developed with NONMEM software using a top-down approach. Historical (previously published) data were used for model development and qualification. In-house individual rich and sparse tacrolimus blood concentration profiles from adult and paediatric kidney, liver, lung and heart transplant patients were used for model validation. Model validation was based on successful numerical convergence, adequate precision in parameter estimation, acceptable goodness of fit with respect to measured blood concentrations with no indication of bias, and acceptable performance of visual predictive checks. External validation was performed by fitting the model to independent data from 3 external cohorts and remaining previously published studies.

RESULTS

A total of 76 models were found relevant for meta-model building from the literature and the related parameters recorded. The meta-model developed using patient level data was structurally a 2-compartment model with first-order absorption, absorption lag time and first-time varying elimination. Population values for clearance, intercompartmental clearance, central and peripheral volume were 22.5 L/h, 24.2 L/h, 246.2 L and 109.9 L, respectively. The absorption first-order rate and the lag time were fixed to 3.37/h and 0.33 hours, respectively. Transplanted organ and time after transplantation were found to influence drug apparent clearance whereas body weight influenced both the apparent volume of distribution and the apparent clearance. The model displayed good results as regards the internal and external validation.

CONCLUSION

A meta-model was successfully developed for tacrolimus in solid organ transplantation that can be used as a basis for the prediction of concentrations in different groups of patients, and eventually for effective dose individualization in different subgroups of the population.

Analysis of Time-Course, Dose-Effect, and Influencing Factors of Antidepressants in the Treatment of Acute Adult Patients With Major Depression

OBJECTIVE

Model-based meta-analysis was used to describe the time-course and dose-effect relationships of antidepressants and also simultaneously investigate the impact of various factors on drug efficacy.

METHODS

This study is a reanalysis of a published network meta-analysis. Only placebo-controlled trials were included in this study. The change rate in depression rating scale scores from baseline was used as an efficacy indicator because a continuous variable is more likely to reflect subtle differences in efficacy between drugs.

RESULTS

A total 230 studies containing 64 346 patients were included in the analysis. The results showed that the number of study sites (single or multi-center) and the type of setting (inpatient or noninpatient) are important factors affecting the efficacy of antidepressants. After deducting the placebo effect, the maximum pure drug efficacy value of inpatients was 18.4% higher than that of noninpatients, and maximum pure drug efficacy value of single-center trials was 10.2% higher than that of multi-central trials. Amitriptyline showed the highest drug efficacy. The remaining 18 antidepressants were comparable or had little difference. Within the approved dose range, no significant dose-response relationship was observed. However, the time-course relationship is obvious for all antidepressants. In terms of safety, with the exception of amitriptyline, the dropout rate due to adverse events of other drugs was not more than 10% higher than that of the placebo group.

CONCLUSION

The number of study sites and the type of setting are significant impact factors for the efficacy of antidepressants. Except for amitriptyline, the other 18 antidepressants have little difference in efficacy and safety.

Predicting the dose of vancomycin in ICU patients receiving different types of RRT therapy: a model-based meta-analytic approach

AIM

Previous pharmacokinetic (PK) studies have proposed various dosing regimens for vancomycin in intensive care unit (ICU) patients undergoing renal replacement therapy (RRT), but all are restricted to specific RRT modalities. To be useful in practice, a population PK model would need to predict vancomycin clearance during any RRT modality. Development of such a model is feasible using meta-analysis of published summarized estimates of vancomycin PK parameters. Our aims were: (i) to develop and validate a population PK model for vancomycin that takes into account any RRT modalities, and (ii) to predict vancomycin dosing for RRT patients in ICU.

METHODS

Vancomycin pharmacokinetics were assumed to be two-compartmental, total body clearance being the sum of non-RRT clearance and RRT-induced clearance. Drug disposition and non-RRT clearance parameters were estimated by systematic review and meta-analysis of previously published parameter estimates. The relationship between RRT-induced clearance and RRT flowrate settings was assessed using a model-based meta-analysis. Prediction performances of the PK model were assessed using external data.

RESULTS

The meta-analyses of disposition parameters, non-RRT clearance and RRT-induced clearance included 11, 6 and 38 studies (84 RRT clearance measurements) respectively. The model performed well in predicting external individual PK data. Individual vancomycin concentrations during RRT were accurately predicted using Bayesian estimation based solely on pre-RRT measurements.

CONCLUSIONS

The PK model allowed accurate prediction of the vancomycin pharmacokinetics during RRT in ICU patients. Based on the model of RRT-induced clearance, an appropriate adjustment of the vancomycin dosing regimen could be proposed for any kind of flowrate settings.

Model-based meta-analysis to evaluate optimal doses of direct oral factor Xa inhibitors in atrial fibrillation patients

The noninferiority of direct oral factor Xa (FXa) inhibitors (rivaroxaban, apixaban, and edoxaban) in treatment of atrial fibrillation were demonstrated compared with warfarin by several large clinical trials; however, subsequent meta-analyses reported a higher risk of major bleeding with rivaroxaban than with the other FXa inhibitors. In the present study, we first estimated the changes of prothrombin time (PT) in 5 randomized trials based on reported population pharmacokinetic and pharmacodynamic models and then carried out a model-based meta-analysis to obtain models describing the relationship between PT changes and the event rates of ischemic stroke/systemic embolism (SE) and of major bleeding. By using the models, we simulated the optimal therapeutic doses for each FXa inhibitor. It was suggested that dose reduction of rivaroxaban from the current 20 mg/d to 10 mg/d would decrease patient deaths from major bleeding (hazard ratio [HR], 0.69; 95% confidence interval [CI], 0.64-0.74) with little increase in those for ischemic stroke/SE (HR, 1.11; 95% CI, 1.07-1.20). The overall decrease in the mortality caused by both events was estimated as 5.81 per 10 000 patient-years (95% CI, 3.92-8.16), with an HR of 0.87 (95% CI, 0.83-0.91). For apixaban and edoxaban, no distinct change in the overall mortality was simulated by dose modification. This study suggested that the current dose of rivaroxaban might be excessive and would need to be reduced to decrease the excess risk of major bleeding.

A Model-Based Meta-Analysis of 24 Antihyperglycemic Drugs for Type 2 Diabetes: Comparison of Treatment Effects at Therapeutic Doses

Model-based meta-analysis was used to compare glycemic control, weight changes, and hypoglycemia risk across 24 antihyperglycemic drugs used to treat type 2 diabetes. Electronic searches identified 229 randomized controlled studies comprising 121,914 patients. To ensure fair and unbiased treatment comparisons, the analyses adjusted for important differences between studies, including duration of treatment, baseline glycated hemoglobin, and drug dosages. At the approved doses, glycemic control was typically greatest with glucagon-like peptide 1 receptor agonists (GLP-1RAs), and least with dipeptidyl peptidase-4 (DPP-4) inhibitors. Weight loss was highly variable across GLP-1RAs but was similar across sodium-glucose cotransporter 2 (SGLT2) inhibitors. Large weight increases were observed with sulfonylureas and thiazolidinediones. Hypoglycemia risk was highest with sulfonylureas, although gliclazide was notably lower. Hypoglycemia risk for DPP-4 inhibitors, SGLT2 inhibitors, and thiazolidinediones was generally very low but increased slightly for both GLP-1RAs and metformin. In summary, important differences between and within drug classes were identified.

Many Flavors of Model-Based Meta-Analysis: Part II - Modeling Summary Level Longitudinal Responses

Meta-analyses typically assess comparative treatment response for an end point at specific timepoints across studies. However, during drug development, it is often of interest to understand the response time-course of competitor compounds for a variety of purposes. Examples of such application include informing study design and characterizing the onset, maintenance, and offset of action. This tutorial acts as a "points for consideration" document, reviews relevant literature, and fits a longitudinal model to an example dataset.

Model-based Meta-Analysis on the Efficacy of Pharmacological Treatments for Idiopathic Pulmonary Fibrosis

Recently, the US Food and Drug Administration (FDA) approved the first two drugs (pirfenidone and nintedanib) indicated for the treatment of idiopathic pulmonary fibrosis (IPF). The purpose of this analysis was to leverage publicly available data to quantify comparative efficacy of compounds that are approved or in development. An analysis-ready database was developed, and the analysis dataset is composed of summary-level data from 43 arms in 20 trials, with treatment durations ranging from 8-104 weeks. A hierarchical multivariable regression model with nonparametric placebo estimation was used to fit the longitudinal profile of change from baseline of percent predicted forced vital capacity (%predicted FVC) data. Pirfenidone and nintedanib were the only drugs identified to have significant estimated positive treatment effects. Model simulations were performed to further evaluate the covariate and time course of treatment effects on longitudinal change from baseline %predicted FVC to inform future trial designs and support decision making.

Good Practices in Model-Informed Drug Discovery and Development: Practice, Application, and Documentation

This document was developed to enable greater consistency in the practice, application, and documentation of Model-Informed Drug Discovery and Development (MID3) across the pharmaceutical industry. A collection of "good practice" recommendations are assembled here in order to minimize the heterogeneity in both the quality and content of MID3 implementation and documentation. The three major objectives of this white paper are to: i) inform company decision makers how the strategic integration of MID3 can benefit R&D efficiency; ii) provide MID3 analysts with sufficient material to enhance the planning, rigor, and consistency of the application of MID3; and iii) provide regulatory authorities with substrate to develop MID3 related and/or MID3 enabled guidelines.