News Report Technology
November 20, 2023

AstraZeneca Launches Health-Tech Division ‘Evinova’ to Speed Up Clinical Trials Using AI

In Brief

AstraZeneca has established Evinova, a health-tech division that will use digital solutions and AI for clinical trials.

AstraZeneca Establishes Evinova, Brings AI to Speed Up Clinical Trials

AstraZeneca announced it has established Evinova — a health-technology division dedicated to incorporating digital solutions and artificial intelligence into clinical trials. The company anticipates that the initiative will result in a reduction of cost and duration for clinical trials.

Evinova’s primary focus will be on introducing market established and scaled digital technology solutions already being used globally by AstraZeneca, to enhance the efficiency of clinical trial design and execution. The goal is to accelerate clinical trial processes that typically extends beyond seven years, with an alarming 80% of trials failing to meet recruitment criteria.

The also unit aims to blend AstraZeneca’s clinical and regulatory experience with extensive expertise in digital technology, encompassing strategy and development, digital product development, data science and AI, user experience design and behavioral science.

In addition to digital solutions, Evinova will offer personalized scientific services, including remote patient monitoring, trial design and consulting services. The new division has already secured collaboration agreements with two prominent global drug-testing entities, Parexel and Fortrea.

Pharma Companies are Utilizing AI for Clinical Trial Success 

Leading pharmaceutical companies are leveraging artificial intelligence to speed up the identification of patients for clinical trials or reduce the required number of participants, thereby accelerating drug development resulting in significant cost savings.

The human studies phase stands out as the most resource-intensive and time-consuming aspect of drug development, involving years of patient recruitment and testing of new medicines. This process can incur costs exceeding a billion dollars, starting from initial drug discovery to completion.

Major players such as Amgen, Bayer and Novartis are harnessing AI to sift through vast amounts of public health records, prescription data, medical insurance claims and internal data — aiming to significantly cut the time required to sign up the patients for trials.

German pharmaceutical company Bayer utilizes AI to substantially decrease the number of participants required for a late-stage trial of asundexian, an experimental drug designed to reduce the long-term risk of strokes in adults.

By linking mid-stage trial results to real-world data from millions of patients in Finland and the United States, Bayer used AI to predict long-term risks in a population similar to the trial. Armed with this data, the pharma company initiated the late-stage trial with fewer participants. Without AI, the company estimated it would have incurred millions in additional costs and taken up to nine months longer to recruit volunteers.

According to AstraZeneca, the digital health market is experiencing an annual growth rate of approximately 14% and is projected to surpass $900 billion by 2032.

Predominantly, this market is driven by research solutions and remote patient monitoring, with additional contributions from activities like screening, diagnostics, disease prevention and digital pharmacies.

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About The Author

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

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Alisa Davidson
Alisa Davidson

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

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