Artificial Intelligence #AI – the new hope for Pharma R&D - By Manishree Bhattacharya @ManishreeBhatt1

Pretty much every article starts with the challenges that pharmaceutical industry across the globe is facing. It is a difficult industry and everybody acknowledges that, considering the time to develop an original drug (10-15 years), the costs involved (last time I checked it was USD 2-3 billion), the high attrition rates of drug candidates (1 out of 5,000 or 10,000 leads make way for FDA approval), the tough regulatory environment which is varied across countries and geographies, and the rising pressures on pricing (pricing advantage for truly outcome-driven therapeutics). All of these, with the looming patent expiry, the imminent entry of generics, and the tantalizing RoIs, make it even more difficult.
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Well, technology is here to rescue. It will be a grave injustice to talk about technology implementation in pharma R&D in just one article, and because AI and ML are the current buzzwords, I thought, maybe, we could specifically discuss the role Artificial Intelligence plays in streamlining and improving success rates of pharma R&D. Before we go any further, let us have a quick look at the drug discovery process and the typical timelines associated.
More often than not, it takes more than a decade (sometimes > 15 years) for a new drug to enter the market. One should not forget if technologies and in-silico modeling are not effectively used in early stages of drug discovery, drug failure at a later stage is a significant waste of time and money. Now, pharma companies have already been using computational tools to conduct ADMET predictions and in-silico modeling, so what new has Artificial Intelligence to offer?
To answer this question, important will be to look at some of the AI initiatives and activities of key pharmaceutical companies. You may find initiatives where pharma companies are scouting for AI innovation via their open innovation program, so if you are a tech start-up, think about it. 
The list is not exhaustive and is only for the purpose of illustration, but one can clearly see that leading pharma companies have already dipped their toes in Artificial Intelligence-mediated drug discovery and development.
Going back to the drug discovery process diagram, let us superimpose the AI-applications across the process.
Artificial Intelligence and Machine Learning algorithms, not only simplify the existing tasks/processes, it saves time, while adding significant value. Let us understand this better.
BioXcel Corporation, a biopharmaceutical company is working on integrating big data and AI into drug discovery process. One such product is EvolverAI which uses AI algorithms for drug discovery to find the best therapy, thus reducing drug failure. Evolver AI uses big data to screen through huge volumes of structured and unstructured data related to genes, proteins, disease pathways, targets, symptoms etc. within the field of Neuroscience. This is followed by creation of meta-data, which contains network-maps, linking pathophysiology of diseases with drugs. These meta-data are then fed into a decision matrix, which compares all the drugs. Using AI algorithms and human intelligence, several hypotheses are built based on the known linkages, of which the best hypothesis gets selected for future experiments and clinical trials, significantly reducing both time and risk of drug failures.
Exscientia, which has partnerships with both GSK and Sanofi, uses AI to learn best practices from drug discovery data, and helps researchers generate drug candidates in much lesser time.
The beauty of such algorithms is in their ability to go though various data-sets – from medical records, publications, clinical trial data, available data on disease pathways and drug-disease correlation to derive meaningful analysis that can help researchers in decision making. Similarly, screening through EHR, current and past clinical trials, and available publications on epidemiology, can help in site selection for clinical trials. Applications are many, and this is still an evolving area, with many developments happening in the stealth mode.
Many diseases such as cancers and neurodegenerative disorders, having high mortality and morbidity, have been debilitating for people across the globe, with pharma companies pouring in significant amount of money, yet with not-so-significant success rates.
Take Alzheimer’s for example, after three large clinical trials for solanezumab, which was called the breakthrough drug candidate, it hasn’t been able to display significant change in patient’s conditions as compared to a placebo. Solanezumab is an anti-Aβ mAbs, that targets Amyloid beta, which is one of the main components of the amyloid plaques found in the brains of Alzheimer’s patients. Does that mean researchers are looking in the wrong place? Is there a need to rethink the disease pathway and establish newer biomarkers to be targeted? THESE are the areas where AI and ML can help.
Similarly, increasingly the drug research community is realizing that not all drugs work on all patients. AI algorithms can help stratify patient population to identify what causes drug efficacy in some patients while nothing really in others - could be due to an aberration, mutation, any specific biomarker – and AI can help recognize the same in the most efficient manner possible.
And that is not all, there is a lot more - we are just scratching the surface, but one cannot deny that these technologies are the next hope for pharmaceutical companies. What do you think?
Source: Nature, Wall Street Journal, MIT Technology Review, Forbes, PR NewsWire, Micar21, SlideGeeks, BenchSci, Xconomy, MedCityNews, Company Websites
[content title="About Manishree Bhattacharya" icon="fa-heart"]
Manishree Bhattacharya
Independent consulting – strategic research, industry analysis, healthtech evangelist, digital thought leadership (ex-NASSCOM, ex-Evalueserve)
Has over 8 years of experience in strategic research across healthcare, life sciences, software products, and start-ups, and has extensively worked with Indian and Global clients, helping in market analysis, digital evangelizing, start-up collaboration, competitive intelligence, and decision making
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Healthcare being one of the most crucial sectors globally has seen immense transformation over the years. The use of modern day technologies in healthcare has made it possible for the physicians to deliver accurate diagnosis along with proper treatment. Virtual reality (VR) and augmented reality (AR) technologies are fast gaining prominence among various sectors, especially the healthcare sector. Over the past two decades, AR and VR have come a long way, with 2016 being a breakthrough year for both. They have revolutionized the healthcare industry with their rapid adoption in various areas of healthcare. It is now possible for the surgeons to see the virtual condition of a patient’s body parts and accordingly conduct minimally invasive surgery that have greater benefits in comparison to the traditional surgeries and treatments. The use of AR/VR modeling and 3D visualization is found to be helpful in the healthcare sector.

Market overview

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Based on type of devices, the head-mounted displays are expected to take up the majority of the market share, and also grow at a high rate over the forecast period. This growth can be majorly contributed to the increased use of HMDs in various applications such as pharmacy management, patient care management, and medical training and education. Also, the use of AR smart glass is further estimated to witness a high growth, thereby boosting the growth of the overall market.

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How is the market progressing, geographically?

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What is driving and restraining the market growth?

The growth of the worldwide market for augmented reality and virtual reality in healthcare is majorly being influenced by the following factors:

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  • Growing penetration of connected devices in the healthcare sector
  • Increasing investments in healthcare AR and VR

Apart from these, growing demand for AR and VR in emerging economies and usage in fitness management is further expected to create an array of opportunities for the growth of this market.

On the flip side, lack of expertise and knowledge among medical practitioners for the adoption of new technologies and incompetence in deployment of AR and VR solutions are the major factors likely to hinder the growth of this market. Moreover, concerns related to privacy of data, social challenges, and lack of compatibility and interoperability between vendors providing AR and VR solutions are the major challenges to be tackled by the players involved in this market.

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Major players and strategies adopted for sustenance

Google (US), Microsoft (US), DAQRI (US), Psious (Spain), Mindmaze (Switzerland), Firsthand Technology (US), Medical Realities (UK), Atheer (US), Augmedix (US), and Oculus VR (US) are some of the major players involved in the global augmented and virtual reality in healthcare market. These companies are increasingly adopting strategies such as major investments in AR and VR in healthcare and new product launches and developments in order to witness sustained growth as well as maintain their market position. Moreover, various other healthcare IT-enabled companies are venturing in this market in order to gain advantage of the high potential growth that this market has to offer.

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