Next generation techniques used for drug design

Changes in the Market

 

Pharmaceutical companies with a large percentage of the market-share have historically been much further ahead than smaller competitors. This is down to their larger budget and significantly bigger Research and Development (R&D) capabilities. However, in an interview with pharmaphorum.com, Indegene’s Vice President Guarav Kapoor highlights how smaller companies can capitalise on their competitor’s growing ‘’unsustainable’’ business practices.

 

 

‘‘[…] based on the pressures we’ve seen from a pricing point of view […] we think that big pharma will have to reinvent itself. […] the cost of sales is extremely high, between 20% and 30% in the traditional rep-based model.’’

 

 

This old-fashioned sales model needs to be replaced with an artificial intelligent (AI) lead platform says Kapoor, in an attempt for new biotech companies to ‘leapfrog’ the competition and secure their market-share. Indegene have created a platform that uses an ‘omnichannel ecosystem’, which is a single platform that can provide the best option for purchase. It uses ‘’advanced analytics for customer segmentation, targeting and then building sequencing, and predictive analytics to drive certain cohorts for prescription’’ continues Kapoor.

Using such a platform, and varying commercial strategy can be difficult for big pharma to endorse. Companies which have functioned in a certain way for decades are less likely to take the risk. Indegene are instead finding more traction with smaller companies which are eager to experiment. They can’t compete with big pharma’s significant cash supply for product launches so Kapoor informs that ‘‘stretching their dollars is vital’’ for success.

Technology shaping the future of drug design

 

Insilico medicine in 2016 started using AI to synthesise and create new drug candidates. The process utilised Generative Adversarial Networks (GAN) and Reinforcement Learning to create novel molecules. Since then, Insilico have spent two years developing the techniques for creating drugs.

‘‘These efforts have been used to design a novel DR1 kinase inhibitor from scratch in 21 days, and pre-clinically validate in 25 days.’’ The total of 45 days to design a drug candidate is on average 15 times faster than even the biggest pharmaceutical companies.

This has revolutionised the pharmaceutical industry, with the ‘AphaGo Movement’ being endorsed by similar companies such as UK-based BenevolentAI, Exscientia, and US-based Google DeepMind and Berg using similar GAN techniques for R&D.

Insilico’s CEO Alex Zhavoronkov highlighted the benefits of this, saying ‘‘The drug discovery process consists of many phases and often takes decades […] our AI can be used in all phases and in some cases leads to superhuman results’’.

The NHS has recently announced its plans to fund a similar programme by injecting £250 million to capitalise on an AI lead lab, and to enhance research and care for the future. ‘‘The lab will work on ways to use AI to improve the detection of diseases and automate admin tasks to free up staff to care for patients, amongst other things.’’

Future skills

 

Technological advances in the pharmaceutical industry, in addition to the AlphaGo Movement has to be at the forefront of new training according to a UK Topol Review, which recommends that a number of clinicians need to be trained, or re-trained according to the new needs of the industry. The report cites that 90% of clinicians utilise some form of digital skill – with varying aspects being currently under no training regime.

 

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