The global Life Sciences Artificial Intelligence Market size is estimated to surpass $324.2 million mark by 2026 growing at an estimated CAGR of more than 13.1% during the forecast period 2021 to 2026. Life Sciences Artificial Intelligence provides potential to improve the health care system especially personalized medicine and drug development. With the implementation of AI it becomes possible for the healthcare organization to drive innovation and achieve various outcomes including hyper-personalized experiences, new sources of growth, and new levels of efficiency. In 2019, the adoption of technologies such as AI has reshaped the life science industry. The innovation in the life science industry will also lead to provide growing potential for healthcare organizations. Artificial Intelligence is proved to be an advanced tool which is reshaping the Life Sciences industry. The rising application in initiating drug discovery and development is fuelling the need for Life Sciences AI industry.
Life Sciences Artificial Intelligence (AI) Market Segment Analysis – By Process
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 development. A particular focus is on third wave processes. 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 especially with regards to clinical research and drug development.
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Life Sciences Artificial Intelligence (AI) Market Segment Analysis – By Application
Drug Discovery is set to dominate the market and grow at a CAGR of 14.8% through the forecast period. The application of drug discovery for identification of unmet medical needs, target identification, personalized medicine, lead optimization and so on in the healthcare sector will propel the life sciences AI market. Tough medication revelation and computational bio and science demonstrating is highly influenced by AI, hold critical potential to convey early bits of knowledge into the activities of the medications. This will consequently improve business execution and downstream exertion. In addition, 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, thus enhancing the drug development processes.
Life Sciences Artificial Intelligence (AI) Market – By Geography
North America region dominated the global life sciences AI market as of 2020. It is due to the presence of significant players namely TwoXAR Pharmaceuticals, NuMedii, Numerate, Inc. and IBM Corporation. These players are focusing on their offerings of advanced platform for the life science industry. The advanced AI platform establishes enhanced drug development programs thus reshaping the life science industry. The pharmaceutical companies are also looking for partnerships, collaboration and joint venture with the AI startups for enhancing the deployment of AI –based technologies in the life sciences market.
Life Sciences Artificial Intelligence (AI) Market Drivers
Acceleration of Advanced Diagnostics and Drug Development
With the deployment of AI in life sciences industry the healthcare is widely being enhanced which is leading to the acceleration of drug development, and further employment of advanced technology for patient diagnosis. The implementation of histopathology image analysis and automated diagnosis, along with the technological process such as digitalization that permits all microscopic magnifications are widely accelerating the life sciences AI market. In addition, the rising use of AI for pattern recognition, combined with complex algorithms and automated immunohistochemically measurement systems, has provided pathologists the ability to analyze more critical patients cases and offer improved personalized medicine. This involvement of AI for critical diagnosis of patients health will prove to provide a positive impact on market growth. The rising advancements in AI and machine learning for the reduction in the time taken for the development, manufacture and launch of latest patient therapies and for reducing the timelines for the overall product development is also driving the life sciences AI market. Recently, scientists are integrating research data, lab data, and clinical data, with new information sources that includes social media and wearables for the process of drug development and also creating a holistic picture of the drug development candidate. Thus, the need for improved ways for acquiring and extracting data in real-time to scientists leads to the extensive use of AI and machine learning. The adoption of AI and machine learning by scientists also makes the decision for drug development more improved and faster, which will accelerate the product development and scale-up process further enhancing the Life Sciences AI market.
Emerging Machine Learning, and Clinical Site Selection along with the Acceleration of Patient Identification
Machine Learning in the healthcare industry has become an important tool for providing up-to-date information on the safety of the products used in healthcare. Most of life science companies are looking forward to enhance pharmaceutical labels (e.g., package insert, patient information leaflets) in an important way to communicate safety information especially in providing personalized medicine. This factor is also leading to requirement of an updated reference label that is necessary for safety reasons, and include multiple considerations such as artwork printing, production run dates and so on for submitting the local product label to the corresponding health authority. Furthermore, companies’ SOP timelines govern submission due dates which are more stringent than what health authorities require, increasing workload and cost. Thus, with the combination of collected data points by the company along with machine learning helps to determine an optimal submission date for the products and leading to the safety of the products.
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Life Sciences Artificial Intelligence (AI) Market Challenges
Lack of Skilled Workforce and Data Issues
in the recent time, as technology is upgrading the need for skilled workforce is also increasing, but majority of the industries are lagging behind in the adoption of new technologies due to the insufficient skilled workforce. The life science industry is also among those industries which is facing challenges in the adoption of AI and other innovative technology, as majority of the highly skilled AI developers are not interested to work in the life sciences industry further hampering the growth of the market. This key factor is also further leading to the requirement of more creative strategies adopted by pharma companies for attracting and retaining AI talent. The other key challenge that is hindering the adoption of machine learning and AI in life science industry is the access of data, which is also regarded as the biggest barrier affecting the growth of the market. According to the Pistoia Alliance, in 2019, scientists identified that more than 24 percent of respondents referred to access to information as the greatest test to AI adoption, and 30 percent referred to absence of skill for performing AI based machine learning and deep learning. In spite of these hindrances, utilization of AI in the existence sciences has expanded in the previous two years, with 70 percent of respondents expressing they are utilizing AI, including AI and profound learning, in some limit, up from 44 percent in 2018.
Product launches, acquisitions, and R&D activities are key strategies adopted by players in the Life Sciences AI Market. TwoXAR, Numerate, NuMedii, IBM, and Envisagenics and others are considered to be the key players of the Life Sciences AI Market
In January 2021, Harlow-based colocation provider Kao Data has added artificial intelligence (AI)-focused startup InstaDeep to its customer roster of high-performance computing (HPC) clients.
In January 2021, Bioclinica, a solutions provider of clinical life science and technology expertise, has acquired Silicon Valley-based Saliency. Bioclinica will integrate the company’s AI technology into its imaging platform to support a growing portfolio of pharmaceutical and medical device clients.
What can be automated, will be automated – initially, there were several steps of drug development and clinical research 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.
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.
The rise of personalized medicine has created opportunities for AI to enhance the care provided to patients.
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