Elsevier has announced a collaboration with ExactCure, a personalised medicine software startup that uses AI technology to reduce medication errors. Using access to PharmaPendium data, which includes searchable FDA/EMA drug approval documents, as well as pharmacokinetic and efficacy data, ExactCure is developing personalised model simulations that will provide information to physicians to improve the dosing of COVID-19 related therapies.
For this collaboration, PharmaPendium is providing 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 personalised 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. In response to this, 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 tremendously helpful for the clinical pharmacologists and frontline doctors in the development of safe and effective treatment.
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