Steve is the Founder of AI4Diversity, an AI expert at ISO and a social media influencer. First, companies began using artificial intelligence (AI) to transform drug discovery. Now, they are jumping into the robotics race. With robots running labs, there can be more experiments performed faster and in parallel, generating high-quality data that strengthens AI's ability to make accurate hypotheses and validate those hypotheses. Ultimately, that means new drugs can get to market faster where they can start helping patients.

Oxford Nanopore (@nanopore): is a sequencing company (spun out of the University of Oxford) valued at around $4,6 billion in London IPO. Oxford Nanopore is offering a technology to analyse any length of native DNA or RNA, and it's the only sequencing tech company to enable real-time analysis, in fully scalable formats--from pocket to population scale. But Nanopore goes beyond sequencing, since ML learning algorithms can be used to extract unknown biology information hidden in the Nanopore sequencing data. On the report of a Financial Times article, the pandemic put Nanopore on the map since its patented technology (MinION the world's first portable pocket-sized sequencing device) was used in identifying and tracking the spread of Covid variants in 85 countries, by sequencing about 18% of all coronavirus genomes globally. In fact, Oxford Nanopore made a gross profit of £26.9m in the first half of 2021 and is now competing with Illumina in a $7 billion market for DNA sequencing, dominated so far by Illumina.

The search for novel therapies has long been a trial-and-error process that costs drug companies a vast amount of time and money. Now, with artificial intelligence (AI) set to transform the pharmaceutical industry more than any other emerging technology, a growing number of pharma and biotech groups are harnessing the cutting-edge tech to minimise the hit-and-miss nature of R&D and discover new therapies with previously impossible speed and accuracy. Pharmaceutical Technology delves into the new generation of drug discovery companies leveraging AI to uncover novel treatments. Founded in 2018 by life sciences venture capital company Flagship Pioneering, Massachusetts-based Generate Biomedicines uses machine learning to accelerate the discovery of protein therapeutics. The company's AI-powered Generative Biology platform analyses hundreds of millions of known protein structures, and uses the learned patterns to create novel protein sequences that form the basis of new therapies.

As Margaretta Colangelo, Partner at Deep Knowledge Ventures, mentions in her recent article'Although pharmaceutical companies spend over $172 billion on research and development annually, over 90% of molecules discovered using traditional techniques fail in human clinical trials. Moreover, 75% of newly approved drugs are unable to cover the cost of development and some analysts predict that ROI in pharmaceutical R&D may hit zero by 2020.' If we accept that this prediction has some good chances to become reality, then we should see the AI as the Deus ex Machina in the field of pharmaceutical R&D to keep a business alive, but also give the invaluable hope of choice to some patients. In this race for life, some firms set the pace trying to test their limits in uncharted waters. Deep Knowledge Analytics, a subsidiary of Deep Knowledge Ventures, an investment fund focused on DeepTech, separates the companies that are solely dedicated to core scientific R&D out of a total of 1000 AI Healthcare companies globally. According to DKA'The barriers to entry in the AI Healthcare industry are lower than for AI in drug discovery and these companies can achieve real results with much less funding and fewer highly specialized employees.'

As Margaretta Colangelo, Partner at Deep Knowledge Ventures, mentions in her recent article'Although pharmaceutical companies spend over $172 billion on research and development annually, over 90% of molecules discovered using traditional techniques fail in human clinical trials. Moreover, 75% of newly approved drugs are unable to cover the cost of development and some analysts predict that ROI in pharmaceutical R&D may hit zero by 2020.' If we accept that this prediction has some good chances to become reality, then we should see the AI as the Deus ex Machina in the field of pharmaceutical R&D to keep a business alive, but also give the invaluable hope of choice to some patients. In this race for life, some firms set the pace trying to test their limits in uncharted waters. Deep Knowledge Analytics, a subsidiary of Deep Knowledge Ventures, an investment fund focused on DeepTech, separates the companies that are solely dedicated to core scientific R&D out of a total of 1000 AI Healthcare companies globally. According to DKA'The barriers to entry in the AI Healthcare industry are lower than for AI in drug discovery and these companies can achieve real results with much less funding and fewer highly specialized employees.'

As Margaretta Colangelo, Partner at Deep Knowledge Ventures, mentions in her recent article'Although pharmaceutical companies spend over $172 billion on research and development annually, over 90% of molecules discovered using traditional techniques fail in human clinical trials. Moreover, 75% of newly approved drugs are unable to cover the cost of development and some analysts predict that ROI in pharmaceutical R&D may hit zero by 2020.' If we accept that this prediction has some good chances to become reality, then we should see the AI as the Deus ex Machina in the field of pharmaceutical R&D to keep a business alive, but also give the invaluable hope of choice to some patients. In this race for life, some firms set the pace trying to test their limits in uncharted waters. Deep Knowledge Analytics, a subsidiary of Deep Knowledge Ventures, an investment fund focused on DeepTech, separates the companies that are solely dedicated to core scientific R&D out of a total of 1000 AI Healthcare companies globally. According to DKA'The barriers to entry in the AI Healthcare industry are lower than for AI in drug discovery and these companies can achieve real results with much less funding and fewer highly specialized employees.'

Traditional drug discovery is a very long and very expensive process involving many tests to determine the safely and efficacy of each new drug candidate. AI is making the hunt for new drugs quicker, cheaper and more effective. Drug companies are already conducting clinical trials for drugs developed using AI. Although no AI for Drug Discovery companies have brought a blockbuster drug to market yet, since many drugs are currently in clinical trials, we could see the arrival of the AI industry's first blockbuster drug as early as 2020. A drug discovered using AI will be tangible scientific validation of the AI approach and will cause a massive increase of investments and capitalization of this industry.

SAN FRANCISCO--(BUSINESS WIRE)--Verge Genomics, a drug discovery company utilizing machine learning to develop new therapeutics, announced today that it has raised $32 million in Series A financing led by DFJ. New biotech investors WuXi AppTec's Corporate Venture Fund, ALS Investment Fund, Agent Capital, and OS Fund also participated in the round. The oversubscribed round brings Verge's total funding raised to-date to more than $36 million. With this round, Emily Melton of DFJ will join Verge Genomics' Board of Directors. Founded in 2015, Verge intersects machine learning, neuroscience, and experimental biology to accelerate drug discovery.