BioXplor’s AI/Cognitive Software Platform accelerates and greatly reduces the cost of discovery research and clinical trials, with a primary focus on rare and inflammatory diseases data.

Projektinformationen

BIOXPLOR

ID Finanzhilfevereinbarung: 878371

DOI

10.3030/878371

Projekt abgeschlossen

EK-Unterschriftsdatum 31 Juli 2019

Startdatum 1 Juli 2019

Enddatum 30 November 2019

Finanziert unter

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Gesamtkosten

€ 71 429,00

EU-Beitrag

€ 50 000,00

Koordiniert durch

BIOXPLOR LIMITED
Ireland

Periodic Reporting for period 1 - BIOXPLOR (BioXplor’s AI/Cognitive Software Platform accelerates and greatly reduces the cost of discovery research and clinical trials, with a primary focus on rare and inflammatory diseases data.)

Berichtszeitraum: 2019-07-01 bis 2019-11-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The pharmaceutical industry as a whole is projected to reach a negative ROI in 2020, due to a 95% failure in drug trials and a cost of $2bn+ to bring a successful drug to market. This productivity decline is causing a major burden on society, in terms of the increasing cost of approved drugs, and lack of new medicines for rare and complex diseases, including cancer, metabolic disease, and neurological disorders. More than 50% of clinical trials fail due to safety and efficacy and due to starting with the wrong drug target. Yet, today, no single tool, platform or database prioritizes drug targets based on safety and efficacy, and no solution exists for the systematic identification of multiple drug targets and the selection of optimal therapeutic strategies for complex diseases.
BioXplor is building a next-gen AI-powered platform, combining emerging CRISPR and DECL screening technologies to solve this problem through better early prediction of efficacy and safety to reduce downstream failure, reduce time to clinic, and improve ROI. By this approach, we encourage drug discovery programs to target more of the 7000 rare and complex diseases at lower cost and risk, with an estimated 70% cost saving per target and a 25x-100x acceleration through data-driven discovery. The impact of this technology can help usher in a new era of drug discovery for complex diseases with unmet medical needs, including cancer, metabolic disease, and neurological disorders, which affect ~80mil people in the EU alone.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The team applied the platform in real-world tests with Pharma and Biotech companies to bring the clinical trials AI to TLR stage 7 and the discovery software platform to TLR stage 8 via 1) Identification of patient responders and adverse events for known drugs (Pharma); 2) Prediction of a novel pathway and multi-target drug for a rare inflammatory fat disorder with the unmet medical needs (Biotech).
During the feasibility study, BioXplor contacted 10 Biotech and Pharma companies to evaluate the opportunity and to define a viable business model to capture market value.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

BioXplor has generated 50,000 structured target databases from literature, databases, and ontologies developed an AI model to predict disease-target matches, and a drug target software platform with visual, search, text mining, hypotheses generation, and trends modules, including cell and animal models, assays and reagents.

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