Global AI For Vaccine Development Market Size (2023 - 2030)

The global AI for Vaccine Development Market was valued at $8.3 billion in 2022 and is estimated to reach $118.69 billion by 2030 growing at a CAGR of 39.45% during the forecast period 2023 and 2030. 

As per our research report, the global AI for Vaccine Development market is being driven by an increase in the incidence of infectious diseases, extensive R&D activities, technological advancements, and the use of AI in healthcare by numerous pharmaceutical and biotechnology companies worldwide. The market is expanding owing to the several benefits of AI in vaccine production, including its ability to identify vaccine targets, facilitate preclinical testing and clinical trials, organize data for researchers, track vaccine distribution, and more. Drug discovery is traditionally an extremely difficult, expensive, and lengthy process (8–10 years on average from research, development, to sale). By examining multiple scenarios across multiple factors at once, AI could play a significant role in reducing the total test process length from years to months. The discovery of medications and the speedy creation of vaccinations can be aided by AI-based drug screening techniques, which can aid in the understanding of crucial aspects of the virus. AI aids in the development of a self-learning platform that is fed by real-time information as well as past clinical and pharmaceutical data.

The molecular structure of medicine is a key factor in drug design endeavors. To develop new medication candidates or reuse those that already exist, insights from information engines are used. Based on many factors including opportunity, expected response reliability, and safety, AI and machine learning algorithms can be used to predict possible targets and identify the most effective one among them. When it comes to big data and machine learning, intelligent algorithms are viewed as tools for support and calculation for molecular applications. Pharmaceutical firms are utilizing artificial intelligence (AI) to streamline and accelerate the process of clinical development. AI might help pharmaceutical firms release drugs to the market more quickly. In addition to its spectacular gene-sequencing job, AI is also being taught to foresee therapeutic efficacy and adverse effects as well as to manage the enormous volumes of paperwork and data required to support any pharmaceutical product.

COVID-19 pandemic impact on AI for Vaccine Development Market

The Covid-19 pandemic has had a significant impact on the AI for Vaccine Development Market. Since 2020, numerous domestic and international research teams and laboratories have been working on creating vaccinations. When the pandemic first broke out, China was severely afflicted, and it spread quickly around the world. In cooperation with Oregon State University and the University of Rochester, the Baidu research team created the AI tool LinearFold. Pfizer brought together the combination of emerging technologies such as artificial intelligence (AI), smart analytics, and automation to deliver a safe COVID-19 vaccine. The six COVID-19-related proteins' structures were predicted by Google's Deepmind using AI technology. This information can serve as a starting point for future research, aid in the creation of vaccinations, and scale up existing treatments. AI has been used extensively for drug research against Coronavirus disease (COVID-19) since the AI platform can prove to be more useful for the identification of potential existing drugs with inhibitory human coronavirus activities by utilizing various learning datasets. In the fight against COVID-19, AI has played a significant role, particularly from a diagnostic and pharmacological standpoint. Researchers are limited by a shortage of data or an abundance of noisy and outlier data as they lack the vast collections of good data necessary to anticipate findings with more accuracy. Organizations all over the world are taking the necessary steps to apply AI for testing, which is driving market growth

MARKET DRIVERS:

The market is expanding owing to the several benefits of AI in vaccine production, including its ability to identify vaccine targets, facilitate preclinical testing and clinical trials, organize data for researchers, track vaccine distribution, and more:

Standard drug testing takes a long time, thus, AI technology is used to speed up the process gradually.  Understanding the virus and its structure and predicting which of its components can support an immune response are both made possible by machine learning systems and computational studies. AI methods can be used to examine the genetic alterations of the virus and comprehend how the virus changes over time; this is particularly pertinent for illnesses like COVID-19, where several viral variations have developed. The process of developing a vaccine requires a lot of data since it is necessary to comprehend both the virus and the immune system's response to it. To determine which viral targets (or epitopes) are most likely to elicit an immune response, machine learning algorithms can examine vast datasets. Scientists create compatible vaccinations after compiling a target list. The most practical vaccine target can be found using machine learning algorithms, which can recognize antigens from protein sequences. AI can help with preclinical testing, dosage calculations, and immune response prediction. Researchers can use AI algorithms to determine the ideal site for clinical trials. For instance, the MIT School of Engineering developed an epidemiological model called COVID-19 powered by machine learning that provides real-time insights into the epidemic and records people's behavior and health status (exposed, recovered, etc.). The potential of AI technology extends beyond vaccine production to include vaccination distribution, delivery, tracking, and counseling.

The market for AI in vaccine development is being driven by an increase in the incidence of infectious diseases, extensive R & D activities, and the use of AI in healthcare by numerous pharmaceutical and biotechnology companies worldwide:

Infectious diseases continue to be a primary cause of death globally, particularly in low-income nations, despite medical advancements. Millions of people die each year from infectious diseases around the world. Since the invention of mathematical techniques, researchers have improved their ability to forecast epidemics, comprehend the unique characteristics of each pathogen, and find promising targets for drug development. Artificial intelligence and its components have received a lot of attention for their improved capacity to identify specific cancer kinds from imaging data. In addition, pharmaceutical and biotech companies are increasingly adopting AI to hasten the development of vaccines or medications.

MARKET RESTRAINTS:

Accuracy-related challenges with data collection, validation, sharing, and training may limit the growth of AI in the vaccine development sector:

The numerous restrictions put in place to protect patient privacy and advance several other crucial concerns make obtaining, accessing, and using data in the context of health care particularly challenging. The majority of hospital systems hire outside developers to create their AI-based algorithms. This indicates that data collected from patients outside the hospital, who may or may not represent the patient population of the hospital utilizing the software, is used to construct the algorithms. Data security, interoperability, and data privacy are just a few of the problems that make it difficult to share data across health systems, which makes it difficult to validate the majority of internal models. Additionally, an algorithm cannot be fair for all of its attributes, which might result in bias and fairness in triage.

High infrastructure investment requirements could limit market expansion:

To carry out AI-based drug discovery processes, high-end workstations and servers (with built-in GPUs, big storage, and Tesla cards) and high-speed connectivity are necessary. To optimize leads, manufacture, and perform high-throughput screening, this infrastructure must be scaled. Factors such as speed, energy consumption, and cost involved in computing decide the ongoing growth of such procedures. Therefore, frontiers of computational power must be higher to accomplish the intended output in terms of establishing new potential processes and links to facilitate drug development.

AI FOR VACCINE DEVELOPMENT MARKET REPORT COVERAGE:

Segmentation Analysis:

AI for Vaccine Development Market – By Application

• Vaccine Exploration/Preclinical

• Vaccine Clinical Developments and Trials

• Vaccine Manufacturing and QC

The first stages of medication discovery frequently entail a filtering procedure based on earlier research and treatments. To identify prospective therapy possibilities, researchers can employ AI to analyze enormous digital libraries of data with a great deal more accuracy than manual processing (such as analyzing the attributes of tens of thousands of pharmacological compounds). Additionally, AI can be applied at these stages for DNA sequencing based on intricate human data, enabling doctors to do genetic matching and immunological response tests.

The vaccine is tested on test groups with a range of features as part of clinical development. Verifying vaccination safety and adherence to medical regulations are part of the regulatory review and approval process. The development of medications in anticipation of widespread distribution is a component of manufacturing and quality control (QC). By fusing AI and sensor-based technology, firms may leverage fine-grained data to improve supply chain efficiency. This reduces the possibility of product spoilage during distribution and aids in preventing demand-supply misalignments in their production operations.

Each of these phases is crucial for making sure the vaccine created is efficient and secure, that any adverse effects are fully understood, and that it can be manufactured at scale and consistently up until the threat of illness has been adequately reduced. The response to emergent health issues has historically been dragged down by the complexity, regulation, and cost associated with each of these stages. The advancements in AI technology have significantly sped up the process. The market is expanding as a result of rising government funding, ongoing research projects aimed at enhancing the vaccine development process, and expanding business development tactics by well-known pharmaceutical firms.

AI for Vaccine Development Market – By End User

• Pharmaceutical & biotechnology companies

• Contract Research Organization

• Research centers

In 2021, the Pharma and Biopharma firms led the market and contributed more than 42% percent of total revenue. These businesses were among the first major players in performing SARS-CoV-2 investigations in the early stages of the pandemic due to their established infrastructure for vaccine research. The significant market share can be attributed to pharmaceutical companies' strong investment capabilities, which facilitated the quick development of the COVID-19 vaccine. Large pharmaceutical companies and biotech firms are working together to help the latter scale up the COVID-19 vaccine's manufacturing process. The major goal of Research institutes is to carry out investigations to discover unique solutions that may be employed in vaccine development. To generate vaccines quickly, they are creating several online tools and evaluating the data generated by them.

AI for Vaccine Development Market - By Region

• North America

• Europe

• Asia-Pacific

• Rest of the World

The market for AI in vaccine development has been dominated by North America in 2022, followed by Europe and APAC owing to its early adoption of cutting-edge technologies. The expansion of this region can be ascribed to various factors, including expanding research and development efforts, funding initiatives, the presence of key players, an increase in COVID-19 cases, and a sizable population base that has received the COVID-19 vaccine. The government's efforts to advance the COVID-19 vaccine program have also contributed to the market expansion. For instance, the US government started Operation Warp Speed, a public-private collaboration for the creation, production, and distribution of COVID-19 vaccinations. Several well-known AI technology suppliers as well as top start-up companies are currently based in North America. Additional market drivers include the region's strong concentration of top pharmaceutical firms like Pfizer, Abbott Laboratories, and Johnson & Johnson, as well as significant R&D investments.

For companies in the AI vaccine development market, emerging markets like China, India, and the Middle East are anticipated to present substantial growth prospects.  The demand for pharmaceuticals in the majority of these nations is anticipated to rise dramatically owing to the rising prevalence of chronic and infectious diseases, rising income levels, and improved healthcare infrastructure. These markets are particularly attractive to businesses whose profit margins are negatively impacted by the stagnation in mature markets, the expiration of drug patents, and rising regulatory burdens.

AI for Vaccine Development Market -  Key Players 

1. Benevolent AI

2. Pfizer

3. Evaxion Biotech

4. AstraZeneca

5. Eli Lilly

6. Moderna

7. Novartis

8. Baidu

9. Exscientia

10. Roche

11. VantAI

12. Sanofi

13. Cyclica

14. PathAI

15. Atomwise

16. BioSymetrics 

Notable happenings in the Global AI for Vaccine Development Market in the recent past:

• Partnership- In January 2022, AstraZeneca and BenevolentAI disclosed plans to broaden their partnership for drug discovery using artificial intelligence (AI) for disease areas, heart failure (HF), and systemic lupus erythematosus (SLE).

• Collaboration-  In January 2022, Exscientia announced a collaboration with Sanofi. Exscientia's end-to-end AI-driven platform and Sanofi's pioneering research cooperation and license agreement will be used to generate up to 15 new small molecule candidates for oncology and immunology.

• Partnership- In April 2022, GlaxoSmithKline (GSK) and PathAI, a digital pathology startup focused on artificial intelligence (AI), announced a partnership to employ PathAI's technology to support the development of therapies for non-alcoholic steatohepatitis and oncology.

• Partnership- In April 2022, CEPI announced a partnership with the NEC Group of Japan to create a broadly protective betacoronavirus vaccine. For the early development of widely protective betacoronavirus vaccine candidates, CEPI will support NEC OncoImmunity AS (NOI), a Norwegian branch of NEC that specializes in artificial intelligence-driven biotechnology, with seed funding of up to USD 4.8 million.

• Partnership- In November 2021, A new strategic partnership between Sanofi and Owkin was announced. It includes a USD 180 million equity investment, four exclusive cancer research programs, a three-year payout of USD 90 million, and subsequent research milestone-based payments. The AI and precision medicine firm Owkin creates top-notch predictive biomedical AI models and reliable data sets. This partnership will help Sanofi's expanding oncology portfolio in key areas like lung cancer, breast cancer, and multiple myeloma to optimize clinical trial design and detect predictive biomarkers for illnesses and treatment outcomes.

• Joint Venture- In March 2020, Exscientia, a leader in artificial intelligence (AI)-driven drug discovery,  announced a collaborative effort with Diamond Light Source, the UK's national synchrotron facility, and Calibr, a unit of Scripps Research (USA), to advance compounds that may quickly develop into effective drugs for the quick treatment of COVID-19.

• Collaboration- In August 2020, BioSymetrics, a biomedical artificial intelligence company that offers clinical insights and aids researchers produce medications with higher speed and precision, announced a partnership with Sema4, a company that focuses on patient-centered health intelligence, and Janssen Pharmaceuticals, Inc. The partnership's main goal will be to use machine learning to anticipate the onset and severity of COVID-19 in various populations.