FDA Is Using Modeling & Simulation. Why Aren’t You?

Axendia Analysis of “Successes and Opportunities in Modeling & Simulation for FDA”

The last thing you want is to lag your regulator and in the case of modeling and simulation, the FDA is far ahead of much of the life science industry.

Where are you?

Does your company still rely on a “build and test” approach that is costly, time-consuming, and limited in the number of scenarios that can be examined?  Are you afraid that FDA will penalize you for using computer modeling and simulation (CM&S)?  Because if that’s holding you back, you couldn’t be further from the truth.

The FDA has long encouraged the appropriate use of CM&S in product areas under its jurisdiction.  A 2011 strategic plan “Advancing Regulatory Science at FDA” listed developing and applying simulation models for product life cycles, risk assessment, and other regulatory science uses as a goal.

1.          Explaining how and where CM&S is used across FDA, and the type and purpose of CM&S used

2.          Presenting a selection of CM&S case studies from across nearly all FDA centers, which demonstrate how CM&S is playing a tangible role in FDA fulfilling its mission

3.          Identifying opportunities for FDA to better harness CM&S in upcoming years by embracing computational advances and new (and big) data streams to develop improved public health solutions

That’s a solid endorsement of CM&S that you can take to your QA and RA teams!

FDA Case Studies Demonstrate CM&S Success

The report details 14 case studies illustrating how CM&S has been used by FDA scientists to protect and advance public health. They represent the use of CM&S in the FDA Centers and show:

1. Use of CM&S for premarket product review, post market assessment, and policy development or implementation.
2. Use of CM&S to answer specific regulatory questions.
3. Development of resources for FDA scientists or for the scientific community.
4. Programmatic efforts around CM&S.

FDA Case Studies

Public Health Assessment via Structural Evaluation (PHASE): a structure-based approach for assessing the risk a new drug of abuse poses to public safety

Synthetic opioids, particularly fentanyl derivatives sold on the street, have led to a significant number of overdose deaths. Unfortunately, there is little to no pharmacological and toxicological data available on the varieties of these opioids. Because of the many derivations of fentanyl and the lack of resources available to conduct experimental research on the various fentanyl analogs, the Center for Drug Evaluation and Research (CDER) opted to develop a computational risk-assessment model. According to FDA’s report, “PHASE can be used to prioritize experimental inquiry into the potential effects of newly identified drugs of abuse and assist with emergency scheduling.”

Modeling and Simulation-Guided Post Market Assessment of Bisphenol-A (BPA)

Bisphenol-A (BPA) has been used in food packaging since the 1960s. Humans have a wide record of exposure to BPA.  Research has linked even low-dose BPA exposure to cardiovascular problems, including coronary artery heart disease, angina, heart attack, hypertension, and peripheral artery disease. Health concerns from BPA exposure have originated from disparate studies and contradictory reporting.  The National Toxicology Program (NTP) partnered with the National Center for Toxicological Research (NCTR) to conduct toxicity testing and pharmacokinetic studies on BPA. The data gathered was used to create a BPA model that ultimately concluded that bisphenol-A (BPA) is safe for the currently authorized food-contact uses.

Predicting the Safety of Drug Impurities Using (Quantitative) Structure-Activity Relationship Models

FDA’s CDER developed manually curated databases of toxicology results linked to chemical structures.  Models were developed from these databases to fill data gaps when standard toxicology studies were unavailable for molecules in pharmaceutical applications. This work with (Q)SAR models has expanded over the last 10 years to the point that (Q)SAR modeling represents a state-of-the-art approach to toxicity evaluation. Its acceptance is a major mark for the use of modeling and simulation in pharmaceutical development.

In Silico Modeling-Based Approaches for Predicting Toxicity Endpoints

Computer simulation approaches enable fast and reliable assessment of the safety or toxicity of ingredients in foods, cosmetics, or other products. At the Center for Food Safety and Applied Nutrition (CFSAN), scientists are using these approaches to evaluate the safety of a large set of chemicals. Two divisions within CFSAN, the Office of Facilities and Administrative Services (OFAS) and the Office of Applied Research and Safety Assessment (OARSA), are using in silico modeling for safety testing in cosmetics and dietary supplements.

Functionalized Anatomical Models for Computational Life Sciences: from the Virtual Family to o2S2 PARC

Computational life sciences (CLS) and in silico tools are the methods of choice to study devices that affect organ function through neurostimulation devices. The Virtual Family is comprised of detailed, static, anatomical whole-body computer models for medical device safety simulations. The Virtual Family is comprised of detailed, static, anatomical whole-body computer models for medical device safety simulations. Advanced virtual functional models have been constructed for the development of novel therapies and devices, and their safety and efficacy assessment.

Risk Assessment for Transfusion-Transmitted Variant Creutzfeldt-Jakob Disease

Variant Creutzfeldt-Jakob disease (vCJD) is a fatal neurodegenerative disease that can infect a person for many years before making them sick by destroying brain cells. Eating beef and beef products contaminated with the infectious agent of bovine spongiform encephalopathy (BSE) is the main cause of vCJD. In 1999, the US FDA recommended deferring blood donors who had traveled to areas with TTvCJD cases.   In 2012, CBER conducted a risk assessment using a model to estimate risk of TTvCJD in the U.S. and the effectives of donor-deferral in the U.S. blood supply. CBER published this risk assessment in 2014.

A Risk-Informed Credibility Assessment Framework for Computational Modeling

CDRH partnered with medical device industry stakeholders to create the American Society of Mechanical Engineers (ASME) Verification & Validation 40 (V&V 40) 2018 Standard, the first consensus standard for evaluating the predictive capability of computational models for medical devices. The standard provides a risk-informed credibility assessment framework that helps an organization or team determine the rigor needed to support using CM&S for a particular application.

A Case Study in System Dynamic Modeling

Modeling and simulation have become part of many of the activities associated with the development of tobacco regulatory science at the Center for Tobacco Products (CTP). For example, a CTP model to project the impact of regulatory activities on the US population, including users and non-users of tobacco products. Modeling and simulation are also used in the review of regulatory submissions seeking authorization order to market a new tobacco product in the US.

Advancing Model-Informed Drug Development Through Quantitative Clinical Pharmacology

Model-informed drug development (MIDD) methods have been popular for years. These methods have the potential to speed drug development and improve patient safety. The FDA was charged with advancing MIDD in PDUFA VI. In response, CDER’s MIDD initiative was created. The program includes policy development, stakeholder engagement, education/training, and research.

Revealing Food Safety Risks and Evaluating Potential Preventive Controls and Mitigation Strategies: Quantitative Risk Assessment Models

The FDA develops innovative models that predict public health outcomes associated with food safety concerns and risk management strategies. This section covers models used in restaurants and in the development of models of alfalfa sprout seeds affected with salmonella. In each case, the model resolved the contamination problems.

Modeling and Simulation-Guided Premarket Product Quality Assessment

A digital twin is, in its simplest form, a model of a system that mirrors its physical twin. A fully developed digital twin has a physical component (e.g., unit operations), a virtual component, and automated data communications between the two. Since 2019, CDER has developed digital twins of the continuous manufacturing lines for several solid oral drug product regulatory submissions.

Homology Modeling and Molecular Dynamics Simulations to Elucidate Interactions Between SARS-CoV-2 Trimeric Spike Protein and ACE2

Severe Acute Respiratory Syndrome Coronavirus-2 (SARSCoV-2) causes coronavirus disease 2019 (COVID-19). Modeling the interactions between the parts of the virus and ACE-2 could help develop drugs to treat COVID-19.

Maximizing the Public Health Impact of FDA Actions: Risk-Based, Data-Driven Decision Analysis Models

The FDA is responsible for policy development and resource allocation for the United States’ foods program.  It uses modeling tools to measure public health risk criteria and to choose models to rank options based on public health risk criteria.   

Complex Innovative Trial Design Pilot Program

The Complex Innovative Trial Design (CID) Pilot Program is a joint CDER and CBER program which is part of FDA’s ongoing commitment under the Prescription Drug User Fee Act (PDUFA) VI to enhance FDA’s capacity to review CIDs. A company selected as a program participant gets two chances to discuss proposed trial designs with FDA experts.

FDA Modeling and Simulation Prospects are Positive

These 14 projects are just a foothold for modeling and simulation at FDA.  As more FDA scientists and employees learn about modeling and simulation, the possibilities for use flourish. Other areas offer prospects for using CM&S tools:

1.  Accelerating the use of modeling in the product development and premarket review stages where it is not being used.
2. Improving internal networks of FDA CM&S users who can train other employees and scientists in the use of the technology.
3. Establish Good Simulation Practice to stimulate harmonization across the FDA, and where appropriate, with international regulatory bodies.
4. Use CM&S to improve FDA’s ability to process its workload and improve resource allocation.
5. Integrate approaches using multiple modeling disciplines relying on data from multiple sources

Industry Leaders are Reaping the Rewards of CM&S

• Payman Afshari, Ph.D. Senior Principal Engineer, Research & Technology, DePuy Synthes
• Anita Bestelmeyer, Senior Director of Corporate Computer-Aided Engineering, Becton Dickinson
• Jeff Bischoff, Ph.D. Director of Biomechanics Research, Zimmer Biomet
• Frank Menendez, Director of Engineering Services, Alcon
• Mark Palmer, M.D., Ph.D. Research Director and Technical Fellow, Medtronic
• Randy Schiestl, PMP Vice President of R&D, Global Technology & Service, Boston Scientific
• Simon J. Sonntag, Ph.D. Co-Founder & CEO, Virtonomy

Axendia’s research report, “The Value of Computational Modeling & Simulation in the Medical Device Industry,” examines how innovative medical technology companies are using CM&S as digital evidence throughout the product life cycle. The report evaluates CM&S’s ability to accelerate the introduction of high-quality medical products to support improved patient outcomes.

It provides a roadmap to the successful implementation of CM&S to drive improvements and accelerate new product introductions in a timely and cost-effective manner while supporting regulatory compliance.

In Brief

“Simulation is digital evidence, not made up stuff,” said Tina Morrison Ph.D., when she was the Deputy Director, Division of Applied Mechanics, OSEL, CDRH, U.S. FDA.  The release of the report, “Successes and Opportunities in Modeling and Simulation for FDA,” shows the FDA back that up as they expand the use of CM&S tools. 

You do yourself no favor by avoiding the use of these tools that can speed your product along the development path and through FDA review.  Innovative medical technology companies are using CM&S as digital evidence throughout the product life cycle.

Fall behind modernization at your peril—the FDA is out front, paving the way. 

When your company is ready to transition to CM&S, Axendia is ready to assist. 

If you are an industry member or regulator, feel free to contact us for a complimentary 30-minute life sciences inquiry.  If you are a technology and/or service provider, contact us to establish an analyst engagement.

We will continue to provide updates on COMPANY as they become available.

Related content:

• FDA: Simulation is Digital Evidence, Not Made Up Stuff
• The Value of CMS in the Med Dev Industry
• FDA Discusses the Use of Digital Evidence to Accelerate Innovation

The opinions and analysis expressed in this post reflect the judgment of Axendia at the time of publication and are subject to change without notice. Information contained in this report is current as of publication date. Information cited is not warranted by Axendia but has been obtained through a valid research methodology. This report is not intended to endorse any company or product and should not be attributed as such.