It is widely acknowledged that artificial intelligence (AI) is expected to revolutionize various aspects of healthcare, ranging from managing appointments with doctors to creating novel medications. However, AI encompasses a broader scope beyond just massive language models (LLMs) such as ChatGPT.
It is highly likely that the influence of AI on biotechnology will extend well beyond the scope of AI applications that are directly used by consumers. Investors stand to gain numerous advantages from this development. Below are my forecasts for how this shift will unfold, and the reasons for its positive outlook.
Credit: Getty Images.
These companies have already started using AI services for biotechnology.
Biotechnology companies encounter various difficulties.
The first requirement is to have several years of experience. exploration and innovation Before making money from selling a new medicine or technology, researchers need to conduct experiments in the laboratory and the clinic. This process requires a significant amount of funding, and the likelihood of a project being successful is lower than the chances of it failing.
Moreover, as a project progresses from initial stages like research and preclinical experiments to clinical trials and further, the costs involved escalate significantly. While conducting a basic experiment in a lab to validate an idea is relatively inexpensive, the expenses rise as the research progresses to preclinical studies involving animal testing. Yet, the expenses surge dramatically when a company moves towards conducting extensive late-stage clinical trials involving human subjects, reaching costs amounting to tens of millions of dollars and sometimes even exceeding this figure.
A significant concern for biotech companies that have not yet generated revenue is the limited amount of cash available. This creates a strong motivation to prioritize programs that are deemed most likely to succeed during each stage of development, as failure would result in the loss of resources that cannot be easily regained. Likewise, in the production of medication doses for clinical trials, the focus is on maximizing the efficiency of spending initially and expanding production capacity later, after the project has demonstrated its viability.
Artificial intelligence (AI) will assist biotechnology companies in overcoming these obstacles by cutting down on expenses related to research and development as well as production. Consequently, this will allow them to progress multiple projects with the same financial resources. A greater number of attempts will lead to more success, resulting in increased profitability. biotech stocks as a category.
Investors should not expect companies to create their own AI solutions for the industry’s challenges. It is more likely that they will delegate important parts of their research and production to biotech platforms that focus on incorporating AI extensively. Recursion Pharmaceuticals is a company that focuses on using AI and automation to discover new drugs. ( RXRX -2.75% ) and Ginkgo Bioworks is the name of the company. ( DNA -6.37% ) .
Recursion’s business model involves utilizing artificial intelligence to assist biotechnology companies in identifying and evaluating potential candidates for the creation of novel therapies.
This suggests that in the future, businesses may be able to reduce their costs during the discovery stage. Recursion argues that by using a data-driven method for lead generation, they can prevent many failures in the later stages, ultimately saving money. If this is proven to be true, and if other platform companies adopt a similar strategy for their customers, there may be fewer cases of biotech stocks plummeting after failing to meet their clinical trial objectives.
Ginkgo’s unique selling points align with a similar pattern seen in the manufacturing industry.
It is stated that customers can reduce expenses by hiring the company to handle a significant portion of the bioengineering tasks needed for establishing biomanufacturing processes. Some of these bioengineering duties might be delegated to artificial intelligence in the future. The company also oversees the manufacturing process using its advanced automated work stations, delivering the end product to the customer, who is able to avoid purchasing costly equipment. Additionally, customers have the potential to cut down on labor expenses as well.
Moreover, there are other companies striving to incorporate AI into the planning, execution, and evaluation of clinical trials. Streamlining tasks such as meeting regulatory requirements and enrolling patients could significantly reduce expenses.
By leveraging AI, biotech companies can significantly cut costs and minimize the risk of issues in various areas, leading to the alleviation of many major challenges and obstacles. bullish for the whole sector.
Do not trust everything you see in writing.
While the efficiency enhancements proposed by AI companies may seem appealing, investors should remember to think critically about the potential impacts.
Biotechnology companies will continue to face limitations in obtaining funding. Conducting clinical trials will remain costly and frequently not achieve their desired outcomes. The expense of large-scale production will continue to be a major factor for numerous industry participants. Additionally, it is important to note that the stock prices of many biotech companies will still decline when issues arise.
In addition, it should be noted that Recursion Pharmaceuticals and Ginkgo Bioworks might not be capable of delivering the tangible economic advantages of AI that they are currently asserting.
Despite this, the increasing complexity of AI in the biopharmaceutical industry could have a significant impact in the future if it manages to reduce costs sufficiently to extend the financial resources of biotech companies. Over time, AI could potentially reduce the risk associated with biotech stocks, providing a strong rationale for optimism regarding the industry’s future.
