Ai Software For Business Intelligence In Pharmaceutical Industry – AI will revolutionize drug development. Why don’t large pharmaceutical corporations patent AI-related inventions?
Investments in AI-related research and development have surged, and AI is widely viewed as crucial to life sciences innovation. Innovators are using AI to model biological systems, forecast drug candidates’ efficacy and safety, evaluate symptoms, control risks, and diagnose diseases.
Pharmaceutical Industry AI Software For Business Intelligence
With the promise and possibly disruptive influence of AI in the life sciences, it’s no surprise that pharmaceutical businesses use AI. The biggest players in this sector are trying to use AI to boost their pipeline, either by developing AI skills in-house, partnering with AI companies, or through industry efforts like Machine Learning Ledger Orchestration for Drug Discovery (MELLODDY), Machine Learning for Pharmaceutical Discovery and Synthesis Consortium (MLPDS), or Alliance for Artificial Intelligence in Healthcare (AAIH).
Artificial Intelligence in the Pharmaceutical Industry
With all the interest in employing AI in medication research, patent filings should increase. Life & Medical Science has the most AI-related patents of any technology sector, accounting for 16% of European patents during the last 20 years (see here for the report complete AI patent at EPO – long-term trend analysis). 10% of Life & Medical Sciences instances are related to traditional medicinal preparations (ie they are classified under the International Patent Classification code A61K). AI is used to drive pharmaceutical innovation. A closer look at who filed this application demonstrates that the high volume of patent submissions is not driven by major pharmaceutical corporations.
Our research of European patent filings shows who has filed AI-related applications in different domains. Only one large pharmaceutical business is among the top 20 issuers of AI-related applications in the Life & Medical Science industry in 2019 and 2020. Start-ups and established IT companies entering the life sciences sector dominate the list of top filers. The biggest pharmaceutical corporations file 2% of Life & Medical Science filings. Of the pharmaceutical businesses that have filed any AI-related application, the most prolific filers have filed 160 applications in the past 20 years, while the top AI filers have filed roughly 10 times that number. Why are pharmaceutical companies not filing more patent applications in the AI field, given all their attempts to integrate AI into their businesses?
Pharmaceutical businesses may prefer developing goods rather than AI platforms. Pharmaceutical companies will likely continue to prioritize patents above development methods.
Does this indicate pharmaceutical corporations will partner with IT businesses to develop AI platforms? As AI platforms improve and make better predictions, traditional pharmaceutical businesses may lag behind new market entrants in medication development.
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Consequently, a pharmaceutical company may build advanced algorithms to aid drug discovery yet maintain them as internal know-how or trade secrets to avoid patent disclosure.
As useful as know-how and trade secrets can be, using them is risky. They don’t defend against competitors who independently design identical strategies, a major danger in a fast-growing business. Not to mention the lack of worldwide trade secret harmonization and the difficulties of safeguarding intellectual property rights following an unauthorized or unintentional disclosure. While breakthroughs in computer processing capacity and mathematical methodologies that underpin AI make previously intractable life sciences problems seem solvable, the currency of AI-powered research is data. Pharmaceutical corporations have decades of confidential data on medication prospects and biological systems. Pharmaceutical businesses generate and manage this data, which, when combined with a sophisticated AI platform, promises to unleash a new wave of innovation in the life sciences.
Pharmaceutical corporations may be comfortable limiting their patent filings to AI technology while AI has established itself, knowing that their data is crucial. But how can traditional pharmaceutical businesses integrate AI into their business models using this data and AI technology? Pharma-tech partnerships are prevalent. The next phase could be major pharmaceutical players buying AI startups. Notwithstanding market advances, the enormous surge in AI patents ensures that patents will protect technology. Is it only a matter of time until major life science corporations submit more AI patents?
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Artificial Intelligence (AI) In Healthcare Market Size 2022–2030
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In her newest piece, Deep Knowledge Ventures Partner Margaretta Colangelo states, “While pharmaceutical companies spend over $172 billion in research and development yearly, over 90% of compounds found using standard methodologies fail in human clinical trials.” 75% of newly authorized medications cannot pay development expenses, and some analysts project pharmaceutical R&D ROI will approach negative by 2020. If this forecast comes true, AI will save pharmaceutical R&D and save certain patients.
In this race of life, some companies set the pace by testing their limits in unexplored waters. Deep Knowledge Analytics, a subsidiary of Deep Knowledge Ventures, a DeepTech investment firm, isolates core scientific R&D companies from 1000 AI Healthcare enterprises worldwide. According to DKA, “The hurdles to entry in the AI healthcare market are lower than for AI in drug research and this company can generate genuine outcomes with considerably less costs and fewer highly skilled workers.” AI for Drug Development companies need experts in biopharmaceutical sciences (biochemistry, biology, biomedicine, etc.) and AI. To bring novel AI-identified pharmaceuticals to market, a corporation needs a robust, specialized team with enough individual abilities and specialists.
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Even for investors, it’s hard to enter this area because the minimum required ability is considerable. Few investment funds grasp the what, why, and how of the industry and the parameters needed to make sound investment selections. There are 260 investment funds that fund 125 AI-driven drug discovery firms.
These businesses may dominate the pharmaceutical industry in the coming years and make groundbreaking new discoveries. From Pasteur to AI, less than 200 years have transformed patient health and quality of life. But, in recent decades, there is a common impression that we are trapped and that every new step needs a big effort. AI in drug development should improve healthcare. Nonetheless, it is a physical law that some stars will become white dwarfs or supernovas sooner than others. This is true:
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