Bayesian Methods in Human Drug and Biological Products Development in CDER and CBER

Ionan, Alexei; Clark, Jennifer; Travis, James; Amatya, Anup; Scott, John; Smith, James P.; Chattopadhyay, Somesh; Salerno, Mary Jo; Rothmann, Mark D.

doi:10.1007/s43441-022-00483-0

Cited by 9 publications

(5 citation statements)

References 13 publications

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“…This approach allows partial extrapolation of the evidence from adults, which has been advocated for ethical reasons and to improve the efficiency of pediatric drug development. [20][21][22] Elicitation of expert opinion to specify informative prior distributions has been recommended to make inferences on the efficacy (and benefit-risk ratio) of an intervention. 36,38 Formal elicitation methods encourage transparent communication on the rationale for believing in the effectiveness of therapy while acknowledging knowledge gaps and uncertainties.…”

Section: Discussionmentioning

confidence: 99%

“…In the analysis presented here, data on the effect of nintedanib on FVC in adults were incorporated in a Bayesian framework to estimate its effect in children and adolescents with fibrosing ILDs. This approach allows partial extrapolation of the evidence from adults, which has been advocated for ethical reasons and to improve the efficiency of pediatric drug development 20–22 …”

Section: Discussionmentioning

confidence: 99%

“…When drug development in adults precedes development in children, partial extrapolation of evidence from adults enables the efficiency of pediatric drug development to be improved. [16][17][18][19][20][21][22] Bayesian statistical methods have frequently been applied in this context. 23,24 These methods allow external information to be "borrowed" for the estimation of a treatment effect.…”

Section: Introductionmentioning

confidence: 99%

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Estimating the effect of nintedanib on forced vital capacity in children and adolescents with fibrosing interstitial lung disease using a Bayesian dynamic borrowing approach

Maher,

Brown,

Cunningham

et al. 2024

Pediatric Pulmonology

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BackgroundThe rarity of childhood interstitial lung disease (chILD) makes it challenging to conduct powered trials. In the InPedILD trial, among 39 children and adolescents with fibrosing ILD, there was a numerical benefit of nintedanib versus placebo on change in forced vital capacity (FVC) over 24 weeks (difference in mean change in FVC % predicted of 1.21 [95% confidence interval: −3.40, 5.81]). Nintedanib has shown a consistent effect on FVC across populations of adults with different diagnoses of fibrosing ILD.MethodsIn a Bayesian dynamic borrowing analysis, prespecified before data unblinding, we incorporated data on the effect of nintedanib in adults and the data from the InPedILD trial to estimate the effect of nintedanib on FVC in children and adolescents with fibrosing ILD. The data from adults were represented as a meta‐analytic predictive (MAP) prior distribution with mean 1.69 (95% credible interval: 0.49, 3.08). The adult data were weighted according to expert judgment on their relevance to the efficacy of nintedanib in chILD, obtained in a formal elicitation exercise.ResultsCombined data from the MAP prior and InPedILD trial analyzed within the Bayesian framework resulted in a median difference between nintedanib and placebo in change in FVC % predicted at Week 24 of 1.63 (95% credible interval: −0.69, 3.40). The posterior probability for superiority of nintedanib versus placebo was 95.5%, reaching the predefined success criterion of at least 90%.ConclusionThese findings, together with the safety data from the InPedILD trial, support the use of nintedanib in children and adolescents with fibrosing ILDs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimating the effect of nintedanib on forced vital capacity in children and adolescents with fibrosing interstitial lung disease using a Bayesian dynamic borrowing approach

Maher,

Brown,

Cunningham

et al. 2024

Pediatric Pulmonology

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“…Other methods include the use of external control arms as an alternative to placebo. 21 , 22 However, establishing historical control groups is challenging in this field due to the frequent introduction of new treatments, and increasing inclusion of patients who have failed multiple therapies into clinical trials. 23 …”

Section: Discussionmentioning

confidence: 99%

Toward Patient Centricity: Why Do Patients With Inflammatory Bowel Disease Participate in Pharmaceutical Clinical Trials? A Mixed-Methods Exploration of Study Participants

Solitano,

Prins,

Archer

et al. 2024

Crohn's &Amp; Colitis 360

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Background A better understanding of motivations to participate as well as recommendations to reduce barriers to enrolment may assist in design of future clinical trials. Methods We developed a 32-item electronic questionnaire to explore motivations, experiences, and recommendations of inflammatory bowel disease (IBD) patients, who have participated in pharmaceutical clinical trials in a tertiary center in Canada over the last decade. We employed a mixed-methods approach that integrates both quantitative and qualitative research methods. Results We distributed a total of 69 e-mails with surveys and received 46 responses (66.6% response rate). Study participants were mostly male (27/46, 58.7%), non-Hispanic white (43/46, 93.5%), with a mean age of 45.5 years (SD 10.9). Most decided to participate in a clinical trial to benefit future patients (29/46, 63.0%). Half of participants (23/46, 50.0%) reported they were worried about the possibility of receiving placebo, although the majority (29/46, 63.0%) understood they could improve on placebo. The most challenging aspect reported was the number and length of questionnaires (15/46, 32.6%), as well of the number of colonoscopies (14/46, 30.4%). Strategies recommended to increase enrollment were reduction of the chance of receiving placebo (20/46, 43.5%), facilitating inclusion of patients who have failed multiple therapies (20/46, 43.5%), allowing virtual visits (18/46, 39.1%), including subtypes of disease traditionally excluded from trials (16/46, 34.8%) and improving outreach to underrepresented populations (13/46, 28.3%). The vast majority (37/46, 80.4%) reported their experience of participation to be better than expected. Conclusions These results should help inform the design of future clinical trials with a focus on patient centricity.

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“…The goal of discussing selected examples in this section is to demystify and normalize the use of Bayesian methods in various scenarios and demonstrate that the risk of using these approaches may not be as high as perceived by some stakeholders, and the advantages may be relevant for efficient drug development. Additional examples of the use of Bayesian approaches in the regulatory setting have been described elsewhere 10 , 11 .…”

Section: Examples Of How Bayesian Methods Are Being Used Effectivelymentioning

confidence: 99%

Application of Bayesian approaches in drug development: starting a virtuous cycle

Ruberg¹,

Beckers

Hemmings³

et al. 2023

Nat Rev Drug Discov

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The pharmaceutical industry and its global regulators have routinely used frequentist statistical methods, such as null hypothesis significance testing and p values, for evaluation and approval of new treatments. The clinical drug development process, however, with its accumulation of data over time, can be well suited for the use of Bayesian statistical approaches that explicitly incorporate existing data into clinical trial design, analysis and decision-making. Such approaches, if used appropriately, have the potential to substantially reduce the time and cost of bringing innovative medicines to patients, as well as to reduce the exposure of patients in clinical trials to ineffective or unsafe treatment regimens. Nevertheless, despite advances in Bayesian methodology, the availability of the necessary computational power and growing amounts of relevant existing data that could be used, Bayesian methods remain underused in the clinical development and regulatory review of new therapies. Here, we highlight the value of Bayesian methods in drug development, discuss barriers to their application and recommend approaches to address them. Our aim is to engage stakeholders in the process of considering when the use of existing data is appropriate and how Bayesian methods can be implemented more routinely as an effective tool for doing so.

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Bayesian Methods in Human Drug and Biological Products Development in CDER and CBER

Cited by 9 publications

References 13 publications

Estimating the effect of nintedanib on forced vital capacity in children and adolescents with fibrosing interstitial lung disease using a Bayesian dynamic borrowing approach

Estimating the effect of nintedanib on forced vital capacity in children and adolescents with fibrosing interstitial lung disease using a Bayesian dynamic borrowing approach

Toward Patient Centricity: Why Do Patients With Inflammatory Bowel Disease Participate in Pharmaceutical Clinical Trials? A Mixed-Methods Exploration of Study Participants

Application of Bayesian approaches in drug development: starting a virtuous cycle

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