As per our research report, the global artificial intelligence in drug optimization & repurposing market size is estimated to be growing at a CAGR of 43% from 2023 to 2030. Despite the economic slowdown during the pandemic, the AI field turned out to be beneficial. Skilled professionals and Research Scientists were hired to detect patterns and for vaccine development. One of the objectives and responsibilities of AI in vaccine development was to study the proteins that comprised the virus, such as the spike protein(s). An AI system could sift through hundreds of components in a complex structure to select the ones that were most likely to evoke a significant immune response. With the increased use of AI in the healthcare industry, it was possible to anticipate early COVID-19 signs and thereby restrict the spread of the virus. It was used to screen and follow patients, as well as anticipate future illnesses, by employing algorithms that analyse data to uncover meaningful trends.
Increasing Adoption has significantly boosted the growth of AI. Data science and artificial intelligence (AI) are becoming increasingly crucial in medication research and development. In addition to developing novel treatments, AI accelerates the work of current drug development and clinical teams, allowing them to make more informed and precise research decisions. In small-molecule drug development, AI may add value in four ways: access to new biology, enhanced or novel chemistry, higher success rates, and faster and cheaper discovery methods. Furthermore, Artificial intelligence can assist researchers in analysing enormous datasets and identifying patterns that would be difficult or impossible to find using traditional approaches. This can lead to more effective therapies. A lot of R&D activities are being provided to develop computational tools to further understand the diseases and develop effective drugs against the same. Secondly, the surge in the number of cases of chronic disease has delved into the prospects of AI. According to WHO, if the current trend continues, chronic diseases such as cardiovascular disease, cancer, diabetes, and respiratory illnesses will account for 86% of the 90 million deaths each year by 2050, representing a staggering 90% increase in absolute numbers since 2019. AI can swiftly grasp how cancer cells gain resistance to anticancer treatments, which can aid in drug development and therapeutic use. AI increases tumour neoantigen detection and tumour immunotherapy effectiveness. Based on clinical data, chest imaging, lung pathology, and pulmonary function tests, AI can assist in establishing diagnosis and predicting outcomes in pulmonary disorders. AI platforms provide valuable insights for drug discovery and minimizing the severity of diseases. Therefore, these factors are projected to enhance and discover more knowledge thereby having a lot of scope in the coming period.
However, the advanced tools used and being developed require substantial amounts of investments which can be the biggest hindrance in the healthcare industry. To produce accurate predictions and choices, AI systems rely on high-quality data. The data used in medication development is frequently insufficient, inconsistent, or biased. This can result in erroneous or unreliable AI algorithm outputs, which might stymie the medication development process. Furthermore, during clinical trials, only a few molecules can be successful in providing accurate data which can bleed the sector dry.
Based on the therapeutic area, oncology is the largest growing in the Global Artificial Intelligence in Drug Optimization & Repurposing Market. This is because many malignancies are predicted and automated using artificial intelligence (AI), which has emerged as a viable tool for enhancing healthcare accuracy and patient outcomes. Deep knowledge-based AI applications in cancer include risk assessment, early diagnosis, patient prognosis estimate, and therapy selection thereby increasing life expectancy. The infectious disease segment is the fastest growing owing to factors like helping with early detection, optimising pharmaceutical and non-pharmaceutical therapeutic tactics, prediction models, understanding infection mechanisms, telemedicine, vaccine development, etc.
Based on technology, machine learning is the largest growing in Global Artificial Intelligence in Drug Optimization & Repurposing Market. Machine learning approaches enhance decision-making in pharmaceutical data across a wide range of applications, including QSAR analysis, hit discovery, and de novo drug designs, to produce more accurate results. Deep Learning, a subset of Machine Learning is the fastest-growing segment in the Global Artificial Intelligence in Drug Optimization & Repurposing Market. SVM is widely used for drug optimization. The capacity of SVMs to categorise active or inactive molecules has allowed substances to be prioritised for virtual screening. DeepPurpose [20] is majorly used for drug repurposing because it helps in drug–target interaction (DTI) integrating encoding-based approaches of drug molecules and protein amino acid sequences.
Based on offering, the service sector is the largest growing in the Global Artificial Intelligence in Drug Optimization & Repurposing Market owing to the demand, time taken, and accuracy associated with the same. The service sector is the fastest-growing sector in the coming years.
Based on end-users, Biotechnology firms and Pharmaceutical Companies are the largest growing in the Global Artificial Intelligence in Drug Optimization & Repurposing Market. This is mainly because of better funding, opportunities, collaborations, advanced technologies and databases. However, research organizations are the fastest growing because of schemes, initiatives and grants being provided by Government bodies.
Based on region, North America dominates the Global Artificial Intelligence in Drug Optimization & Repurposing Market owing to huge investments, economy, advanced research, increasing adoption, collaborations and partnerships. USA and Canada are the top leading countries. Asia Pacific is the fastest growing because of changes in regulations, grants, funding, and research activities regarding the concept of personalised medicine. China is a Tier 1 country with the most AI centres and is undergoing national digitization in the healthcare industry.
Companies playing a leading role in the global artificial intelligence in drug optimization & repurposing market profiled in this report are Microsoft, IBM, Exscientia, GNS Healthcare, Alphabet, Benevolent AI, Cloud Pharmaceuticals, NVIDIA Corporation, DEEP GENOMICS, and Cyclica.
Oncology
Neurodegenerative Diseases
Cardiovascular Disease
Genetic Diseases
Metabolic Diseases
Infectious Disease
Others
Machine Learning
Deep Learning
Support Vector Machine (SVM)
DeepPurpose 20
Natural Language Processing
Virtual Screening
Others
Services
Softwares
Biotechnology firms and Pharmaceutical Companies
Research Organizations
Academic Institutes
Others
North America
Europe
Asia-Pacific
South America
Middle East and Africa
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