A Landscape of Artificial Intelligence (AI) In Pharmaceutical R&D

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Machine Learning


Marshall Pillay joins OKRA

   by Marina Gonzalo    140
Marshall Pillay joins OKRA

Cambridge, UK, October 5th 2020 - OKRA is thrilled to announce the appointment of Marshall Pillay as VP Commercial - Europe and International. Starting today, Marshall will join OKRA from AKTANA, where he was most recently GM of Europe, responsible for all business and operations in the continent.

The AI Productivity Game in Pharma

   by Amandeep Singh    380
The AI Productivity Game in Pharma

The pharmaceutical business is one of the riskiest industries to venture into. Drug discovery is an artisanal process where a carefully designed drug takes about 10 years and approximately 2.5 billion dollars to be approved and launched into the market. The complexity of biological systems places the odds at a ridiculous failure rate of 90%. In recent years, the declining efficiency of the R&D efforts has put the pharma industry on its toes. 

In the past decade, Artificial Intelligence (AI) has already revolutionized several industries, including automotive, entertainment and fintech. AI dictates routes and ETA on google maps, executes multiple stock exchange transactions, enables facial recognition, and powers the voice assistants Siri and Alexa. However, the adoption of AI in pharma has been restricted due to limited data available about what works (the successful 10%) and the innate complexity of the process of drug discovery.

OKRA raises ambitious target to 6 million predictions in Life Sciences by end of 2020

   by Marina Gonzalo    106
OKRA raises ambitious target to 6 million predictions in Life Sciences by end of 2020

Cambridge, UK, September 29th 2020 - Following on from June's breakthrough news that OKRA hit its target of 2 million validated predictions at >95% accuracy a full 6 months early, the company has set its sights on a record-breaking 6 million predictions completed by year end. This means that pharma companies have benefitted from an unparalleled level of support during the most uncertain time in recent memory, using predictions to guide their staff to take the right next step. This is 1 million more than the revised target set only in June.

[Interview] Expediting Drug Discovery Through Advanced Machine Learning

   by Andrii Buvailo    437
[Interview] Expediting Drug Discovery Through Advanced Machine Learning

The application of next-generation data analytics tools, powered by machine learning and artificial intelligence (AI) components, has become a long-term strategic priority for most companies in the pharmaceutical and biotech industries. However, such systems have to make sure the organisational data is findable, accessible, interoperable, and reusable across different sub-systems, applications, departments, teams, and even companies. 

Aigenpulse, a technology company at the forefront of data management and analytics in the Life Science industry, has built a portfolio of tools for working with organisational research data at scale and accelerating the discovery and development of better targets and candidates using advanced machine learning technologies.

Aigenpulse launches data analysis suite to automate flow cytometry

   by Aigenpulse    552
Aigenpulse launches data analysis suite to automate flow cytometry

11th September 2020: Life science and data technology innovator, Aigenpulse, is launching its CytoML Experiment Suite – an automated, end-to-end, machine learning solution specifically aimed at streamlining and automating cytometry analysis at scale and replacing manual gating processes. With it, users will benefit from a single point-of-truth about all cytometry data across any organisation.