Currently there is no miracle drug out there to cure COVID-19 [1]. Drugs such as the anti-malarial, Hydroxychloroquine, have shown to be helpful based on “anecdotal evidence” [2]. However, scientists are still debating its efficacy, and some have warned of the dangers of authorizing the use of such drugs too quickly in the absence of wider studies. The side effects can be severe – especially in the case of overdose. Much more research is needed, but time is short, and the use of model simulations based on patient specifics and for diverse candidate drugs could be a game changer.

In response to this need, Elsevier and ExactCure [3], a personalized medicine startup that uses AI technology to reduce medication errors, are announcing a new collaboration. Using data from PharmaPendium, which includes searchable FDA/EMA drug approval documents, as well as pharmacokinetic and efficacy data, ExactCure is developing personalized model simulations that will provide information to physicians to improve the dosing of COVID-19 related therapies.

“We have been working with a university hospital in the south of France to provide the clinical pharmacologist and pharmacist the simulation-based suggestions,” says Fabien Astic, co-founder of ExactCure, “This allows them to quickly adapt their treatment decisions for a safer and more efficient use of these promising drugs, that while currently still under investigation, could potentially be critical and life-saving for many COVID-19 patients. Through this collaboration with Elsevier to use PharmaPendium’s data we can accelerate this really important work.”

PharmaPendium will provide ExactCure with pharmacokinetic information for approximately 20 approved drugs that have been widely cited in the literature and the news, such as Hydroxychloroquine, Chloroquine, Lopinavir/Ritonavir and Azithromycin, including their regulatory-approval datasets. ExactCure will use this data to build drug-specific exposure models that allow the prediction of pharmacokinetic properties (e.g. Cmax, AUC, Tmax etc).

The first step is to build a simulation based on the patient age, weight, drug dosage, dosing time and end-time, resulting in a personalized therapeutic window between efficiency and over-exposure. This could potentially reduce the number of adverse drug events. Furthermore, the simulation will be enriched by adding more patient parameters, such as renal status, which is also a critical factor for many severe patients.

“As the pandemic deepens, hundreds of clinical trials have been set up to test existing medications against COVID-19,” comments Olivier Barberan, Director Translational Medicine Solutions at Elsevier. “Elsevier has taken its work further by sharing PharmaPendium data to support ExactCure in building the ‘digital twin’ that simulates in-silico the efficacy and interactions of drugs in the body of a patient based on their personal characteristics. This can be extremely helpful for the clinical pharmacologists and frontline doctors in the development of safe and effective treatment. We are looking forward to continuing this work with ExactCure to help reduce the impact of this global pandemic.”