NEW YORK—Global information analytics business Elsevier is working together with a set of evaluation partners that includes industry leaders such as Boehringer Ingelheim, Eli Lilly and Co., Pierre Fabre, Sanofi, Servier and others to develop a new and improved drug-drug interaction risk calculator (DDIRC). The updated DDIRC will help drug metabolism-pharmacokinetic (DMPK) and clinical pharmacology scientists improve patient safety and outcomes and reduce risk during pharmaceutical development.
Adverse drug reactions (ADRs) are a serious problem worldwide, noted Elsevier, pointing out that in Europe, 197,000 deaths per year are attributed to ADRs. The FDA estimates that over 106,000 people die every year due to ADRs and, in the U.S. alone, the cost to the medical care system is an estimated $200 billion per year. One reason for the increase in ADRs is the growth in prescription use, especially among aging populations where drug-drug interactions (DDIs) are more likely. Currently, 9 percent of Americans over age 55 take 10 or more drugs, which greatly increases the likelihood of DDIs and ADRs.
As such, Elsevier noted, pharmaceutical companies not only have to ensure that their drug is safe for use and effective at treating its primary targets, but they also have to ensure that that same drug is equally safe and effective when interacting with potentially thousands of other drugs—an ever-more difficult task.
As DDIRC is a “mechanistic static” modeling calculator, it reportedly can be used to predict interactions early on—when information on the drug candidate is limited—through to later stages of drug development. It also allows fast predictions, for quick responses to questions from regulatory bodies or physicians.
“Elsevier’s PharmaPendium team has collected the background data, and the DDIRC can potentially help us put that data to work to broadly understand DDI implications,” said Jessica Rehmel, a consultant scientist with Eli Lilly. “We look forward to quickly evaluating and helping to develop this quantitative risk assessment tool.”
This joint project between Elsevier’s PharmaPendium team and a group of leading pharma companies will develop and test, for the first time, a new DDIRC that can analyze both internal and external data. It will include additional models that can, for example, assess the risk of transporter-mediated DDIs or better assess the risk of DDIs due to polypharmacy, and will deliver accurate, shareable and actionable insights.
“Because patient safety has always been a priority for Servier, we want to make sure that our drugs are optimally co-administered. Predicting pharmacokinetic drug-drug interactions with the maximum of relevance, precision and reactivity is therefore essential,” declared Yannick Parmentier, head of the Biopharmaceutical Research Department at Servier. “It starts by anticipating the risk at the research stage, including it in the decision process, to mastering the benefit risk ratio in development phase, optimizing clinical DDI trials as well as following up potential combinations with new drugs appearing on the market in the clinical practice. DDIRC is therefore an essential tool in those perspectives and enables rapid responses, hence decisions, on the interaction risks. In addition, because the tool will be used by a large community of users, it will allow also to harmonize the way to predict DDI to the benefit of the patient.”
“The healthcare industry’s ability to treat more and more ailments has enabled people to live longer and more fruitful lives, but with that benefit also comes the grave risk of complications when those drugs interact,” said Guenther Kurapkat, senior vice president of Life Science Solutions at Elsevier. “Researchers developing drugs need tools that can take their valuable internal data and cross-reference it against what’s available in public regulatory filings to get a broader view into how their drugs may interact with others. That’s why we are developing this new DDIRC alongside the pharma companies who will depend on it to ensure that key decisions are made with the most predictive insights.