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Using Predictive Tools To Bring Drugs to Market Faster

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Approximately 90% of drugs evaluated in clinical trials fail to reach regulatory approval, with new drugs taking 10–15 years to reach the market.

Translating preclinical research findings to patients using predictive tools can help drug developers by reducing animal testing, improving drug safety and increasing successful regulatory submissions. These tools can help pharma companies predict adverse events, examine pre-clinical and clinical data and benchmark drug candidates against competitors – helping to inform decisions and accelerate drug development.

We spoke to Olivier Barberan, director of Translational Medicine Solutions at Elsevier, to find out more about how predictive tools can inform pharma companies and help pave the way for drugs to get to market.

Sarah Whelan (SW): Could you briefly introduce what PharmaPendium is and what its main applications are?

Olivier Barberan (OB): PharmaPendium is an online platform used by pharma professionals and researchers that supports translational science and accelerates drug development by combining extensive preclinical and clinical data with predictive tools. It has three main applications:

  • Facilitates decisions about drug safety and efficacy in research by compiling detailed scientific literature, regulatory data, clinical trial databases and real-world evidence on similar drug targets.
  • Enables the benchmarking of competitor drugs by collating critical facts around drug candidates, targeted outcomes of trials and their development pipelines.
  • Helps to develop effective strategies that increase the success of regulatory approvals – with access to documentation covering current requirements, past approvals and safety signals related to a drug. PharmaPendium includes complete US Food and Drug Administration (FDA) and European Medicines Agency (EMA) approval packages.

SW: What improvements have been brought about with the launch of the new PharmaPendium? How does it differ from its previous iteration?

OB: We know from talking to our customers that the transition from preclinical to clinical trial stages continues to be a challenge. Manual curation of documents to support regulatory submissions is time-consuming and submissions have a high rate of failure, with 93% of drugs entering clinical trials failing to secure regulatory approval. When developing the new PharmaPendium, we wanted to tackle these challenges by enabling researchers to seamlessly access all the data they need – regulatory, safety and competitor data – in one place.

We also set out to make PharmaPendium as user-friendly as possible. We now have a quick search bar with autocomplete to cover all datasets, including quantitative and structured data, and text searches for items like regulatory labels. A new tab-style display streamlines navigation and allows researchers to cross-reference complex data within seconds, and new charts and graphs make it easy to visualize and quickly interpret data.

SW: Can you explain how PharmaPendium’s predictive tools enable the translation of preclinical research findings into clinical trials? How can this streamline the process toward regulatory approval?

OB: PharmaPendium features two predictive tools. The Drug–Drug Interaction Risk Calculator (DDIRC) uses data from clinical trials, adverse event reports, medical records and scientific literature to predict a drug candidate’s interactions with other medications. By formatting predictions to be compliant with major regulators like the FDA, the Pharmaceuticals and Medical Devices Agency (PMDA) and EMA, the DDIRC speeds up time to approval. We’ve seen the DDIRC in action at Sanofi/DDNi, where the tool was used to accelerate approvals for fexinidazole, a drug to treat sleeping sickness. The results of in vivo simulations were used to characterize the risk of in vivo interaction of fexinidazole with co-medications. These predictions were used in submissions and enabled Sanofi/DDNi to deliver the new medications for sleeping sickness to Uganda and the Democratic Republic of the Congo with record speed.

PharmaPendium’s second predictive tool is the new Safety Margin Tool. It assesses off-target adverse drug reactions (ADRs) and secondary pharmacology effects during drug development, enabling pharma companies to make informed decisions and take necessary precautions to ensure patient safety.

The tool analyzes in vitro secondary pharmacology and exposure data from marketed and withdrawn drugs to calculate a safety margin. By comparing a drug candidate to defined safety margins, researchers can anticipate off-target ADRs in humans and adjust their regulatory filings, eliminate the need for unnecessary trials and reduce safety hazards within the early phases of drug discovery.

PharmaPendium’s Safety Margin Tool provides a visualization of secondary pharmacology risk assessment for drug candidates.

PharmaPendium’s Safety Margin Tool provides a visualization of secondary pharmacology risk assessment for drug candidates. Credit: Elsevier.

SW: How is PharmaPendium being used to reduce the number of animal studies involved in drug development?

OB: PharmaPendium supports the 3Rs initiative to replace, reduce and refine animal testing. It allows organizations to understand which models were optimal in comparable drugs, so toxicologists can reduce the need for testing. Additionally, the Safety Margin Tool allows teams to predict possible ADRs more accurately in humans by analyzing existing data from non-animal experiments. This eliminates the need for unnecessary animal testing during secondary pharmacology.

SW: PharmaPendium is described as being trusted by regulatory agencies and top pharmaceutical companies. Could you elaborate on how these institutions have benefited from using PharmaPendium in their drug development processes?

OB: At the time of writing, the majority of large pharmaceutical companies worldwide use PharmaPendium to accelerate their drug development processes by quickly compiling information that previously would have taken months of research. With PharmaPendium’s packaged data and predictive tools, collecting information on toxicity, adverse events, dose selection and more now only takes half a day, significantly reducing costs and increasing the rate of success.

Regulatory agencies, including the FDA and PMDA, also use PharmaPendium to support best practices during the approvals process. For example, regulators can look at PharmaPendium to compare another regulator’s practices around certain drug categories, symptoms and routes of administration to their own standards. PharmaPendium also improves the scientific knowledge of regulators, such as through developing predictive models around drug, symptom or complication categories.

SW: How can organizations incorporate PharmaPendium’s datasets into their workflows? For example, to shorten development timelines or reduce costs?

OB: PharmaPendium makes workflows easier by providing data in standardized, machine-readable formats that can be directly incorporated into organizations’ systems via secure APIs, alongside the web platform. This means PharmaPendium data is ready to go, no matter which systems are in place at a company. Having such high-quality, interoperable datasets saves significant time that would have otherwise been spent reformatting data and supports AI applications.

Dr. Olivier Barberan was speaking to Dr. Sarah Whelan, Science Writer for Technology Networks.

About the interviewee:

Dr. Olivier Barberan is the director of Translational Medicine Solutions at Elsevier and is responsible for the development of PharmaPendium. He has over 20 years of experience in the pharmaceutical industry and holds an engineering degree from Ecole Centrale Marseille and a PhD in medicinal chemistry from Paris-Sud University.