Manishree Bhattacharya

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.





Pic Credit: CreativeCommons.org

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

The article was first published on Ms. Manishree Bhattacharya’s LinkedIn Pulse Blog, here. Its been republished here with the authors’ permission.

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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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Blog Series: #IoT in Healthcare by Manishree Bhattacharya @ManishreeBhatt1


The opportunity for #IoT in Healthcare is estimated to be $2.5 trillion by 2025. How are we embracing this change? The Types of Opportunities that present themselves to the Startups, Healthcare IT organisations are tremendous.

During the #PhilipsChat, on the 10th April 2017, we asked the experts what they thought about the current trends and focus areas that the IT Industry, Medical Device Manufacturers, Hospitals and Start-ups will need to keep in view, in the near and short-term, while making their organisation ready for the Digital Transformation that can be and will be enabled by #IoT in Healthcare.  
Presenting the insights shared by Manishree Bhattacharya (@ManishreeBhatt1) on #IoT in Healthcare

Q1: In the near term (1-3 years), What are the top 3 innovations in IoT that can benefit healthcare?
Manishree Bhattacharya: 1. Remote monitoring of (cardiac disorders, COPD, Alzheimer’s, Parkinson’s, insomnia, diabetes, elderly, expecting mothers)
2. An integrated/connected surgical room, where devices are interoperable, regularly feeds in data into patient profile in EMR, to streamline post-operative care, both in the hospital and beyond, at patient homes
3. IoT for ensuring drug/treatment adherence, such as sensor-based pills
Q2. Do you see any device, connected via any protocol and with any cloud; as the future, if yes how will that be achieved? Standards?
Manishree Bhattacharya: Right now, developments are quite random and sporadic. To achieve larger goals, moving from connected devices to connected hospitals, some level of standardization and uniformity will be important to ensure an error-free, and secured transmission.
Q3: In India (or your country), what are the Digital Infrastructure requirements for enabling IoT based Innovations in Healthcare?
Manishree Bhattacharya: Seeing Digital Health take off in India in its full bloom is one of my wishes, and the preliminary requisite would be to encourage hospitals go paper-less – have EHR systems implemented, with a timeline set for nation-wide implementation. Just imagine how seamless healthcare delivery will be if primary, secondary and tertiary centres are integrated – data can seamlessly flow from one centre to another. Government has a very strong role to play here, that will help in creating the right infrastructure, timely adoption, establishing standards, lowering costs by promoting local manufacturing, and boosting HealthIT start-ups.
Q4. Please share use cases for Connected Care for: Healthy Living, Prevention, Diagnosis, Treatment, Homecare:
Manishree Bhattacharya:
Healthy Living – Most consumer IoT devices aim to do that – tracking exercise regimes, diet plans
Prevention – Say a heart patient puts on a wearable device that continuously monitors and sends signals to nurses/doctors for any aberration – this can ensure timely treatment and prevent a severe episode.
Homecare – A person who has just had a surgery, and is on homecare – his regular vitals, diet plan, outputs are remotely being tracked by the doctor/nurse – who can selectively revise the diet or post-surgery recovery plan. Same goes with elderly who are on home-care.
Treatment – A sensor-based pill that sends a signal to a care-giver on ingestion of the pill.
The bigger purpose – We know that not all medicines work on every patient. Regularly tracking patients not only help in timely interventions, and more personalized treatments, it also opens routes to more clinical research on personalized medicines.
Q5: What are the Healthcare based Smart City components? How can Local, State and National Government’s make #IoT solutions in healthcare economically viable?
Manishree Bhattacharya: Answering to how can government make IoT solutions viable, my thoughts would be:
  1. By promoting indigenous manufacturing to curb costs
  2. Incentivising IoT adoption in hospitals
  3. Prioritizing HealthIT in the overall start-up agenda
Q6: How can private hospitals justify the RoI’s of Smart Hospital Components?
Manishree Bhattacharya: By improving quality of care; reducing hospital re-admissions, yet prolonging the care process that extends to one’s home; and finally improving patient engagement/adherence. A patient is more likely to visit a doctor who can provide a more personalized treatment than the one who cannot. Important would be define these key metrics/KPIs right at the beginning of implementation.

Q7. Tell us a 5 Year view of IoT in Healthcare and what would a Patient Experience be in a Smart Hospital?
Manishree Bhattacharya: First, we have to understand the purpose of IoT in healthcare – it is not there just for the sake of it, but to truly enable a coordinated and long-term care, that would eventually reduce mortality, morbidity, and hospital re-admissions. Patient experience is bound to improve. A patient will not have to run from one department to another, narrating the whole problem and showing multiple reports. So when a cancer in-patient enters a psychologist’s office, and the doctor already knows the problem, and also has the latest vitals of the patient right in his tablet, he knows that the patient was not able to get any sleep the previous night and has a high BP right now. The doctor would hence probably choose to talk about things that can ease the patient’s current situation. Now, that is truly an enriching experience.

Looking ahead in the future, we may also have AI-enabled voice assistants that will make a patient more comfortable in hospital settings.
Q8. Finally: What areas of IoT based innovations are you looking to partner with Startups for? Can you give us two areas?
Manishree Bhattacharya: Would love to connect with any start-up that can provide meaningful solutions for the Indian healthcare landscape. What I would also like to see is how these start-ups are using the tonnes of data that IoT devices generate, in deriving meaningful analysis – big data, AI, and so on.

References

  1. Here is the original Blog Post announcing the #PhilipsChat Tweetchat : http://blog.hcitexpert.com/2017/04/philipschat-on-iot-in-healthcare.html
  2. 3 ways in which Information Technology can improve healthcare in India by Manishree Bhattacharya (@ManishreeBhatt1) on NASSCOM Community
  1. IoT in India – The Next Big Wave by NASSCOM http://www.nasscom.in/iot-india-next-big-wave
  2. Curated list of Tweets from the #PhilipsChat: https://twitter.com/i/moments/852242427008233473
  3. Review the #PhilipsChat Transcript & analytics via @symplur here >> http://hcsm.io/2loNiv7
Stay tuned to the #IoT in Healthcare Blog series. Bookmark this link to follow on the insights being shared by the experts on the HCITExpert Blog:

http://blog.hcitexpert.com/search/label/IoT%20in%20Healthcare

Author
Manishree Bhattacharya

Manager – Research & Advisory at NASSCOM
Business professional with 7+ years of experience in research and advisory, across IT, healthcare, and medical technologies. At NASSCOM, responsible for identifying digital opportunities, driving thought leadership/innovation and delivering actionable insights for the Indian Technology Industry
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