Coronavirus Disease 2019 (Covid-19) continues to rapidly claim lives and challenge the limits of our knowledge and our healthcare system. Therapy currently consists of supportive care, while several FDA-approved drugs are being rapidly investigated in clinical trials with the hope of repurposing them. Even during outbreaks such as this, investigational approaches should be guided by sound rationale and rigorous and unbiased scientific vetting.
Here is presented a unique approach to understand the emerging features of COVID-19 and use those insights gained to precisely tailor disease management and inform drug discovery. The approach involves the use of a fundamental and powerful mathematical principle, i.e., Boolean Equivalent Correlated Clusters (BECC) to sift through human transcriptomic datasets and extract a universal (invariant) gene expression signature that is associated with acute CoV infection which resolves during convalescence.
An approach was developed that is geared to overcome the above-mentioned challenges using a few in-built features: (i) Unbiased and rigorous; it uses an informatics approach to sift through > 50,000 datasets to identify insightful and actionable patterns/signatures from ‘big’ data; (ii) Precise, because it uses a quantitative criteria, set by mathematical logic and statistical cutoffs; (iii) Rationalized, because it not only takes into consideration how SARS-CoV-2 breaches the host cell, but also the host immune response that is mounted in response to such a breach. (iv) Targeted, because the approach first formulates a precise therapeutic goal before screening for drugs that can achieve such goal; (v) Predictive, of whether or not any targeted intervention takes us towards or farther from the desirable therapeutic goal; and (vi) Rapidly translatable, because when used in conjunction with in vitro human screening platforms as Phase ‘0’ models, it can interpret and validate drug efficacy. This approach has not only allowed pinpointing predisposing conditions and vetting beneficial vs. harmful diets and drugs, but also objectively weighing in on ongoing controversies, pinpointing high priority drugs, and predicting prospectively the outcome of several ongoing and planned clinical trials.
This technology is available for non-exclusive licensing.