Life Sciences Artificial Intelligence (AI) Market - Forecast(2020 - 2025)

 The Life Sciences AI Market is estimated to surpass $239.1 million by 2024, growing at an estimated rate of 14% from 2018 to 2024. The AI in life science industry is majorly driven by the efforts put to develop automation systems, among others. Growing interests towards artificial intelligence is also set to propel the market growth in the future.

Currently, Artificial Intelligence (AI) is in the growing stage, but it is showing significant growth in life sciences industry in the upcoming future due to rising application in initiating drug discovery and enhancement. As, Life Sciences are full of high-end processes, Artificial Intelligence is used to manage, gather and very nicely utilize all the structured and unstructured data.

Implementing artificial intelligence with life sciences industry is growing rapidly, and now with the chance to transfer old processes over discovery, enhancement, manufacturing and regulation, to take medicines immediately to the patients. Very tough drug discovery and computational bio and chemistry modeling influenced by AI, hold significant potential to deliver early insights into the workings of the drugs. This will automatically enhance business performance and downstream effort.

Mainly, lengthy and high cost enhancement processes is the main area where artificial intelligence can be influenced to augment trail managers to effectively manage typical global operations, trail designing and planning, risk predictions, examining and CAPA, and to gain significant efficiencies. Artificial intelligence  has faced rising adoption as it reduces time and costs. These technologies however are yet to be significantly adapted in the Asia Pacific region.

This report incorporates an in-depth assessment of life sciences AI market by type namely, three-wave process, end-user applications and geography. The major terms in life sciences AI encompassed in the scope includes various diagnosis and disease identification, personalized medicine, drug discovery and manufacture, clinical trials, radio therapy and radiology, and electronic health records.

What are the major applications for Life Sciences AI?
The various end users assessed include drug discovery, pre-clinical, clinical, drug approval, patient monitoring and others. A broad range of asset tracking applications in faster drug discovery which are currently being explored includes many safety precautions, and target identifications, which are raising the market of the Life Sciences AI, and estimated to have huge growth during the forecast period. The capital expenditure of major companies in the discovery of diseases and safety measures have also escalated significantly since the last decade.



Market Research and Market Trends of Life Sciences AI
  • In upcoming future, the main goal is to introduce the most impacted trends which are affecting the market of the AI in the life sciences industry.
  • As, the technology is in advanced position, the trends related to AI-powered drug discovery in the life sciences industry are getting a very less similar responses. The following are the main trends which leads AI to emerge in life sciences.
  • What can be automated, will be automated - initially, there were several steps of drug discovery which are very expensive to perform, which took time and were labor demanding. If pharmaceutical companies starts different stages along with automation automatically it will save money, time and rises success rates
  • Unified Machine Learning Models – Building Unified Models will support the estimation of future behavior of compounds and their performance in confused clinical trials. Mainly, there are 2 stages which are accessible: estimating toxicity and estimating efficacy of combined therapies.
  • Lack of AI-Skilled Labor – Many high-skilled and also very talented AI developers are willing to work with the life sciences industry. The life sciences industry will not only be attractive, but also very interesting, and the developers who worked with this industry will become new entrepreneurs.
  • Commodification of the Data – There is an option of many regular public data sets like PubMed, Clinicaltrials.gov, and US patent office filling data. These had been resolved by AI companies, making the data set, mainly interchangeable. Some companies with their investments in the quality of modification of these data sets are dispersing themselves and also in their ability to fix at a time orthogonal data sets like genomic or expression data.
  • Table Stakes – Now, it is fully estimated that a vendor will be performing some aspect of machine learning to their data or services. Table stakes are taking place many times in pharmaceutical research as well, especially in computer vision and automated tasks. The variation should not be there that AI is being applied, but how well it is being applied.
  • Startups and tech companies take the lead in AI-Powered Drug Discovery – Growing internal experiences in deep learning and reinforcement learning is very tough as the expert scientists are showing interest in achieving the results very faster, and also very few deep leaning experts with too much intelligence in biomedical sciences.
  • Big Pharmaceutical Companies switch from partnerships to acquisitions – In 2017, almost each and every big pharmaceutical company announced a partnership with one or more AI startups. 
  • China takes the lead – China is the leading country which is developing greatly in the AI sector, when compared to other countries because of high investments in the field and heavy interest with a high population. 
  • Adapting AI talent in China has now become very costly, and there are many pharmaceutical companies which were looking forward to incorporate AI in drug discovery. And also, it became mandatory for the executives to get an international outlook of the AI industry, looking beyond the most similar hubs such as Boston and Silicon Valley.
Who are the Major Players in Life Sciences AI?
Some of the major companies included in the report areTwoXAR, Numerate, NuMedii, IBM, and Envisagenics.

What is our report scope?
The report incorporates in-depth assessment of the competitive landscape, product market sizing, product benchmarking, market trends, product developments, financial analysis, strategic analysis and so on, to gauge the impact forces and potential opportunities of the market. Apart from this, the report also includes a study of major developments in the market such as product launches, agreements, acquisitions, collaborations, mergers and so on, to comprehend the prevailing market dynamics at present, and its impact during the forecast period 2018-2024.

All our reports are customizable to as per the company needs, to a certain extent, we do provide 20 free consulting hours along with the purchase of each report, this which will allow you to request any additional data to customize the report to as per your needs.

Key Takeaways from this Report
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