Biotechnology is one of those fields that find themselves underreported unless the result of some new study is "shocking" or a potential new cancer cure is found. The reality is often far less sensational but exciting nonetheless.
As the field continues to grow, there are plenty of interesting trends and developments you might like to keep an eye out for:
Gene Tech
You might have heard of CRISPR or CRISPR/Cas9; this recent development in the field of gene editing has made front-page news across the world—for good reason. CRISPR is possibly the most famous biotechnological innovation of the 21st century. This article is simply too short to explain how the system works in its entirety—and developments are constant, but the future is bright. Put very simply, CRISPR stands for clustered, regularly interspaced short palindromic repeats, which is a technology that scientists use to modify the DNA of living organisms.
In December 2023, the first therapeutic application of CRISPR was approved by the FDA. It is called Casgevy, and it is a treatment for sickle cell disease. This treatment has paved the way for new FDA applications for CRISPR treatments, which could soon be approved as trials for Hepatitis B, E. coli infections, and multiple cancers have been underway for some time.
Big Data in Biotech
When it comes to the giant data sets produced and analysed on a daily basis, biologists, statisticians, and data scientists alike make a massive impact with new biotech innovations.
As the field grows, so does the amount of data generated and, often, the complexity. It is the job of data scientists to find new ways to process large data sets effectively, whether it's AI, new architectures, techniques, algorithms, or analytics.
As demand for high-quality data scientists steadily rises, there are a range of new courses like online data science masters that make quality education more accessible—and often more accessible—than ever.
Artificial Intelligence (AI)
The variety of uses for AI in most fields is immense. In biotech, AI is already being used to transform data and analytic processing for drug trials. Many argue that by using AI and machine learning to streamline and enhance the clinical trial process, drugs can be developed faster and at a higher quality.
Perhaps the most exciting news surrounding AI in biotech is its ability to compose DNA sequences. This technology identifies the order of nucleotide bases in DNA or RNA, encoding hereditary information for protein production. AI's role is to understand the relationship between a gene's nucleotide sequence and the resulting protein shape, which is crucial for protein function. Misfolded proteins can lead to diseases, and AI's ability to predict protein shapes can aid in understanding these diseases and developing treatments that are far more likely to work than previously.
The integration of AI with gene editing is enabling the design of bespoke proteins-suited to highly specific jobs. Scientists can modify bacteria to act as so-called 'mini-factories,' producing new proteins with potential applications such as reducing greenhouse gases, digesting plastics, or acting as species-specific pesticides. This combination of AI and gene editing is set to shift biotech into high gear, opening up new possibilities in the field.
Drug Trials
If we are going to mention how AI is transforming the drug trial industry, then we should also look at the industry itself. Drug trials are nothing new and are not biotechnological innovations in themselves; however, the way drugs are developed, trials are run, and results are processed to produce useful results is a world unto itself.
Biotech introduces methods like in-vitro testing and computer simulations, predicting drug effects without extensive human trials. AI streamlines this process by automating data collection and analysis.
The final stage of any drug trial—processing the results, is being transformed rapidly from a time and resource-consuming process to a more streamlined one powered by AI. Biotech provides detailed insights into drug-body interactions at a cellular level, and AI processes these complex data sets, identifying patterns that might be missed by humans. As these technologies advance, drug trials will become even more efficient and precise, leading to faster development of new drugs and safer, more effective treatments for patients.
Neuralink
Imagine an implant that creates a seamless interface between the human brain and a computer—this is Neuralink, or it will be soon. Elon Musk, the world's richest man and founder of Paypal, Tesla, SpaceX, and now Neuralink, will go down in history for so many reasons—and now he can add Neuralink to the list. Neuralink has now been successfully implanted into a human—that's right, a small device the size of a coin has been successfully implanted into someone's skull—connecting the brain to a computer, but how exactly does it work, and what are the applications?
Musk's stated aim with Neuralink is to "Create a generalised brain interface to restore autonomy to those with unmet medical needs today and unlock human potential tomorrow." What this means for now is to restore some function to those who have lost it. The first patient, Noland Arbaugh, lost control of his limbs after a driving accident. After having the Neuralink device implanted, Mr. Arbaugh has the ability to move a computer cursor with his mind.
To move a cursor with one's mind requires a lot of neural activity to be monitored. This is where Neuralink's technology comes into play. The device connects to the neurons in the brain by ultra-thin threads. These threads are capable of detecting and recording the electrical signals that neurons produce when they are active.
When Mr. Arbaugh thinks about moving the cursor, specific neurons in his brain fire off. Neuralink's device picks up these signals and translates them into commands that the computer can understand. This translation process is facilitated by machine learning algorithms that have been trained to recognise patterns in neural activity. Over time, the algorithms become more accurate, enabling smoother and more precise control of the cursor. This is how Neuralink is able to bridge the gap between the human brain and a computer, opening up a world of possibilities for restoring function and autonomy to those with unmet medical needs.
The rise in AI, gene editing, neural interfaces, and the rapidly changing drug trial industry are just a few key areas trending in biotechnology, and discoveries continue to grow exponentially. At the end of the day, biotech is all about the interplay between engineering, biology, chemistry, physics, computer science, and so many other disciplines. To keep up with the rapid speed and tenacity of development, we need more scientists, as well as other STEM disciplines, to fill the countless opportunities across these fields and develop the future technology.
