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.
The companies that lead the way
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.’ AI for Drug Discovery companies need much higher levels of expertise in traditional biopharmaceutical science (biochemistry, biology, biomedicine, etc.) and in core AI techniques. To achieve the “full stack” required to bring new AI-identified drugs to market, a company needs very strong, very specialized teams, with both sufficient individual expertise and a sufficient total number of specialists on board.
But even for investors, it is difficult to enter this sector because the minimum required expertise barrier is comparatively high. There are very few investment funds that truly understand the what, why and how of the industry and the parameters required to make reasonable investment decisions in the sector. There are probably fewer than 20 among the 260 investment funds that have financed the 125 active AI in Drug Discovery companies.
A hard game to play but the winner takes money and glory
Maybe in the next few years, some of these companies will have a strong presence in the pharmaceutical sector, achieving unprecedented breakthroughs in drug development. From Paster to AI less than 200 years of developments have elapsed that radically altered healthcare and patients’ quality of life. However, during the recent decades, there has been a widespread feeling that we have stuck and every new step needs enormous effort. Hopefully, AI in drug development will boost healthcare to new heights. Nevertheless, it’s a physical law that some stars will end up white dwarfs or supernovas, sooner than others. This is a fact that has to be always in the back of our mind when we see a star being born.
Note: Deep Knowledge Analytics applies quantified metrics to industry analysis and uses mathematical equations to compare multiple parameters and more than 100 factors to differentiate levels of maturity, business development and scientific/technological advantages in an objective way.
