(2 of 4) Transitioning from Clinical Research to FDA Review: Clinical Data Application Assembly Team

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Are you planning, or currently in, the process of building your submission clinical data package for a New Drug Application (NDA) or Biologics License Application (BLA)? It can be a complicated process, and in this blog series, we are discussing some of the most important considerations to keep in mind while preparing for FDA submission of clinical data and analytics. Our last post covered the process of preparing the application deliverables to showcase all of the safety and efficacy evidence on your new biologic or pharmaceutical. This time, we are looking specifically at the team members you will need to assemble to ensure the process is smooth and flawless.

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(1 of 4) Transitioning from Clinical Research to FDA Review: Preparing Submission Deliverables

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The process of developing new pharmaceuticals and biologics is long-drawn, pricey, and heavily regulated. After drug discovery and years of pre-clinical and clinical research, a regulatory authority, such as the U.S. Food and Drug Administration (FDA), must review all animal and human data regarding a product’s safety, efficacy, and biological mechanisms. Successfully achieving market approval requires not only a safe and effectual therapy but also accurately presenting all of the evidence to prove it works and is safe for use. In this blog series, we will be reviewing some of the most important components necessary for filing a New Drug Application (NDA) or a Biologics License Application (BLA): the deliverables, the people, the timeline, and the budget. Today, let’s start with the deliverables.

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6 Tips for Communicating with the FDA During Product Development

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If you are reading this, you are likely in the process of developing a new medication or medical device for FDA approval. Maybe your product is nicely progressing through pre-clinical trials and you’re in the process of building your clinical trial protocols. Maybe you’re evaluating the pharmacology and toxicology data, or maybe you’ve already submitted the IND. But have you reached out to your Regulatory Project Manager (RPM) at the FDA yet?

Communicating with the FDA is an important aspect of clinical research and provides the opportunity to assure your research is following all regulatory and safety guidelines. The RPMs are the primary points of contact between you and the FDA and will facilitate the resolution of conflicts or concerns between you and the review team. They can also offer advice throughout the development process on topics ranging from clinical and statistical protocols to safety and product quality. Read more

(4 of 4) Network Meta-Analysis Series: Model Implementation

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Model Implementation with Network Meta-Analysis:

We will fit our model using WinBUGS and SAS version 9.4.  For the Bayesian implementation we will employ the binomial likelihood for dichotomous outcomes and will use uninformative prior distributions for the treatment effects, and a minimally informative prior distribution for the common heterogeneity SD depending on the outcome. Also, we will assume uninformative priors for all meta-regression coefficients. We will check for convergence using appropriate MCMC diagnostics.

GRADE quality assessment of all comparisons in the network:

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(3 of 4) Network Meta-Analysis Series: Assessing Data

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Risk of bias assessment

We will use the tool described in the Cochrane Collaboration Handbook to assess risk of bias in the included studies.  The assessment will be performed by two independent reviewers and any disagreement will resolved by consensus. We will evaluate the risk of bias in the following domains: generation of allocation sequence, allocation concealment, blinding of study personnel and participants, blinding of outcome assessor, attrition, selective outcome reporting and other domains, including sponsorship bias. Where inadequate or insufficient details of allocation concealment and other characteristics of trials are provided, we may contact the trial authors to obtain further information. Read more

Is Enrichment Beneficial for ALS Research? We Say “Yes!”

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Earlier this year, the FDA released updated guidelines on the types and use of study population enrichment methods. They believe the use of enrichment can potentially provide increased efficiency in the clinical trial process. Our experts at Princeton Pharmatech have proven these benefits, at least in the development of Edaravone, a product approved in 2017 for treatment of amyotrophic lateral sclerosis (ALS). Read more

(2 of 4) Network Meta-Analysis: Statistical Synthesis of Study Data

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Characteristics of included studies:

We will generate descriptive statistics for the trial, and study population characteristics across all eligible trials, describing the types of comparisons and some important variables, either clinical or methodological (such as year of publication, age, severity of illness, sponsorship and clinical setting).

We will present the evidence in the network diagram using graphical tools that allows for appropriate visual representation of the included studies. To understand which are the most influential comparisons in the network and how direct and indirect evidence influences the final summary data, we will use the contribution matrix that describes the percentage contribution of each direct meta-analysis to the entire body of evidence. Read more

(1 of 4) Network Meta-Analysis Series: Relative Safety and Efficacy of New Marketing Drugs

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Background

Network meta-analysis provides a global estimate of effectiveness of intervention regimes, by establishing a network between regimes combining both direct and indirect evidence from trial studies.

Meta-analyses of randomized controlled trials are considered the top of the hierarchy of clinical evidence.  However, oftentimes, head-to-head comparisons are not available or are insufficient to answer a specific clinical question. NMA overcomes this limitation by providing a global estimate of efficacy or safety of multiple intervention regimes that have limited or no direct comparisons. Furthermore, NMA allows for ranking of the intervention regimes to allow for identification of the best option amongst all available options, provided that the statistical inference is valid. This appeals to clinicians and other decision makers as NMA can be used to answer the important question of “Which treatment is the best or worst?” Read more

Making Sense of the FDA’s Real World Data Program

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Since the passage of the 21st Century Cures Act (aka Cures Act) in 2016, the FDA has been releasing new protocols and programs to expedite the approval process for new medical drugs and devices. One such new program is the Real-world Evidence (RWE) program that allows for the use of data collected outside of clinical trials to be incorporated into research submitted for FDA approval. In December 2018, the FDA published a framework for the RWE program in which they delineate the potential of RWE to support the approval of new indications for products already on the market, and post-approval study requirements.  Read more

Six Factors that Determine if a REMS is Needed

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Yesterday, April 4th, 2019, the FDA issued new industry guidance for Risk Evaluation and Mitigation Strategy (REMS). This final guidance clarifies how the FDA applies six factors in determining whether a REMS is required for a particular drug and what type of REMS might be necessary (i.e. what specific elements or tools should be included as part of the REMS) to ensure that the benefits of a drug outweigh its risks. If the drug has been shown to be effective but is associated with a specific serious risk, REMS might be required to manage and mitigate a specific risk. Read more