Tag: AI IN PHARMA

The Impact of AI and Data Analytics in Pharma Research

The Impact of AI and Data Analytics in Pharma Research

AI in pharma research has the potential to be a veritable game-changer for the entire sector. Data analytics in pharmaceuticals along with other innovations like data-driven research and AI/machine learning in pharma have made it comparatively easier to develop new drugs and tackle emerging diseases. Biopharma research remains expensive and lengthy although AI can play a vital role in enabling higher probabilities of success and boosting productivity.  How AI and Data Analytics are Indispensable for Pharma Research Here are a few ways in which AI in pharma research can be indispensable for the industry soon. AI in pharma research will enable the creation of feedback loops for further refining the predictive abilities and stability of AI algorithms. They will also inform experimental design functions accordingly. Through analytics and data science tools, pharma can capture the entire value of the present portfolio and create mechanisms and IP for driving research in the future. AI-drug discovery is already taking place with several companies building their pipelines. Biopharma entities are also developing top-down and executive strategies where AI-backed discovery can be a vital indicator and enabler of performance in the future. Automated image analysis or lead optimisation will be bolstered along with the collection of experimental data in a reusable manner, automated screening algorithms linking molecular descriptions with hits or desired outputs, blueprinting, enabling better testing and learning solutions for product delivery and designing new screening protocols. AI is already transforming the research space through the application of machine learning and data science to huge data sets, enabling swifter discoveries of newer molecules. It enables cross-referencing of published scientific literature with alternate sources of data (clinical trial data, conference abstracts, public databases, and unpublished data) to surface therapies that are promising. Medicines can be delivered in months at times instead of several years as a result. AI can also help lower clinical trial costs and cycle times while enhancing overall clinical development outcomes considerably. ML and AI are already being used for automatically generating study protocols while NLP (natural language processing) is being used to scale up manual tasks. AI algorithms can also ensure continual clinical data cleaning, coding, aggregation, management, and storage. Through automation and centralisation of intakes for adverse event reports backed by AI-backed technologies like NLP and OCR (optical character recognition), case documentation workloads are considerably reduced for expediting investigative processes. These are only a few of the widespread benefits that data analytics, AI, and ML can bring to the table for life sciences and pharmaceutical companies, especially in terms of research and development. FAQs What role will AI play in optimising clinical trials and research methodologies, and how is this expected to impact the pharmaceutical industry in 2024? AI will play a huge role in the optimisation of research methodologies and clinical trials in the future. This will have a positive impact on the pharmaceutical industry in 2024 and beyond since AI will optimise patient recruitment, predict the efficacy of treatments, automate data analysis, and boost safety tracking. It will also accelerate trial procedures while lowering costs and enhancing data quality. This will lead to more personalised and successful clinical trials. How will integrating AI and data analytics accelerate drug discovery processes within the pharmaceutical industry in the upcoming year? Drug discovery processes within the pharmaceutical industry can be accelerated in the upcoming year through the integration of data analytics and AI. This will be possible through the prediction of drug-target interactions, evaluation of the safety and efficacy of drugs that are repurposed, and identification of newer options for treatments. Potential biomarkers can be identified while researchers can easily analyse big data sets and design new molecules while forecasting the efficacy levels of potential drug candidates accordingly.

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Life Science & Pharma News Wrap | Weekly Snippet

Life Science & Pharma News Wrap | Weekly Snippet

✅ Scientists unveil a new tech for detecting protein modifications. From disease research to drug development, this discovery can now delve deeper into vital biological pathways. https://www.news-medical.net/news/20230801/Scientists-develop-breakthrough-technology-for-detecting-protein-modifications.aspx ✅ Hyderabad’s thriving ecosystem is offering boundless opportunities for growth and breakthrough research. No wonder, more than 12 big biotech companies are now eyeing this city to expand their footprints. https://m.timesofindia.com/city/hyderabad/its-destination-hyd-for-top-biotech-life-sciences-firms/articleshow/102241355.cms ✅ CHA Vaccine Institute and Pharos iBio join hands to co-develop AI-based treatments. This collaboration aims to reinvest immunotherapies for a healthier future. https://www.koreabiomed.com/news/articleView.html?idxno=21757 ✅ PIPA and Meati are set to redefine how we approach life sciences and food innovation. Powered by AI, this transformative journey promises the way for personalised and more effective treatments.https://www.koreabiomed.com/news/articleView.html?idxno=21757

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INT. Pulse

INT Pulse

Dear Colleague, there you are at your desk, starting the day with a review of your 80/20 list and suddenly –  upcoming meeting alert – or in other words, the sound of your workday dying.  Fret not, because just like you, your boss hates that sound too.  Nope, we didn’t cook this up ourselves – multiple researches stand by what we’re telling you.   Executives spend an average of 25 hours a week in meetings, yet nearly half of those video calls and project updates could disappear without any negative impact, per a survey of over 10,000 desk workers by Future Forum.   Reluctantly going to noncritical meetings wastes about USD100 million a year at big organisations, according to another survey.  The studies found the top reason why business leaders went to unproductive meetings is that they thought it would be a good use of time, but ultimately wasn’t.  They also attend because they’re afraid to miss something important, and to show their own manager they’re working.   Reminds us of that old saying – ‘this meeting could have been an email’.  Just like the one you are reading now.  AI: Why Google Is Taking It Nice And Easy What You Know The once-a-little-known startup, OpenAI, took on Big G head-on in a fight for the spot as AI’s top dog.  Within just 60 days of its release, ChatGPT amassed 100 million+ users worldwide. Also, since it saw daylight, ChatGPT has passed multiple prestigious graduate-level exams in law and business, even going as far as passing the United States Medical Licensing Exam (USMLE).  On the flip side, Google recently released an ad for Bard (it’s own AI tool) that had incorrect information coming directly from the chatbot, resulting in the loss of over USD100 billion in market value for the tech giant. What You Also Know Even with an unspectacular tech stack, ChatGPT’s decision to offer AI to the masses through the web has revolutionised text generation through automation, having big ramifications on sectors like education, employment, and, particularly relevant to Google, the evolution of online searches.  On the other hand, Google has only allowed some groups to test out Bard before its full public release in the near future.  Plus, Blake Lemoine, an ex Googler, stirred up a storm by publishing a document in which he proposed the possibility of the AI being sentient. (ChatGPT had its share of lobotomy as well, BTW) What You Don’t Know ChatGPT might be winning the AI race for now, but soon Sam Altman will probably have to fly to Washington DC and spend afternoons with an 85-year-old farmer-turned-Senator from Idaho, to explain why his great-granddaughter was suspended from private middle school for using something called “the GPT AI.”  Jokes apart, our resident AI/ML lead, Dipak Singh, is doing some transformational work for enterprises with ChatGPT, Analytics and Artificial Intelligence in general. Reach out to Dipak to explore a solution for your organisation BFSI: Apple Is Ummm, A Bank Now? For all practical considerations, yes.  Let us explain. Sometime back, Apple drove an armoured cash van through the American banking industry.  Yeah?  True. While the average bank is paying less than 0.5% on savings accounts, the USD2.6 trillion tech giant announced it would dish out 4.15% (that’s 10X the national average) annual returns to savers. This, when regional American banks are balking in the wake of the Silicon Valley Bank crisis to maintain their deposit bases, and cash-starved fintech startups are gasping for breath.  Is It A Gravity Game Changer? Pretty much. Per Forbes, “as trust in traditional banks falters, the two most iconic names in tech and finance are joining together to create what might become America’s mightiest FinTech.”  Clarification on the other iconic name – since Apple does not have a banking license, it has teamed up with Goldman Sachs Bank, USA.  In pure fintech jargon, Apple is now a neobank like Jupiter and Fi Money – except its ginormous brand strength, with over two billion iPhones globally, is now serving as Goldman’s branch network.  At 4.5%, Where Are The Profits? Apple’s 10X returns savings account is less about profits than it is about bringing more iPhone owners under Apple and Goldman’s financial umbrella.  While two billion people around the world own Apple devices, fewer than 10% are Apple Card users, meaning there is a megatron* market opportunity waiting to be tapped already.  Net earnings from interest margins may not be Goldman’s priority either.   Profits or no profits, the iPhone user is certainly not complaining.  *megatron is a myth, but it sounds so cool, we used it for effect.  Pharma: Unable To Pear The Loss Pharma technology pioneers, here’s a reality check – one that is brought to you, courtesy, insurance companies.  What The Eff? Yes, Pear Therapeutics, creator of 3 FDA-cleared prescription apps to help treat substance use disorder and insomnia, just announced that it is, err, bankrupt, as the tech startup struggled to get insurers to pay for its technology.  Btw, we are talking about America here.  While doctors were willing to prescribe digital therapeutics and patients were willing to use them, “that isn’t enough,” Pear’s CEO Corey McCann wrote in this LinkedIn post.  “Payors have the ability to deny payment for therapies that are clinically necessary, effective, and cost-saving.” What made Pear special? Clinical robustness: Through high quality clinical trials, Pear demonstrated enhanced patient outcomes in substance use disorder and insomnia. Regulatory blessing: One of the earliest to get US-FDA approval, Pear saw 10,000+ prescriptions written for its digital solution. Investor enthusiasm: Pear raised USD300M in equity, USD100M in debt and went public last year with a valuation of USD1B+. Key Takeaway? Per Tushar Sadhu on LinkedIn, “external capital comes with its powers and responsibilities. Unrealistic valuation and pre-mature IPO undid the good work the company had done in product creation.”  Stuff We Are Watching  GoI’s Chatbot Plan: The Government of India is working to create a multilingual ChatGPT-like chatbot helpline that can be used to manage grievances of disgruntled consumers.   USD100,000 Saved by AI: ChatGPT use cases now run into millions, populating every nook and corner of social timelines, but how does

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