The biotech investment picture
Though VC funding has declined slightly since the highs of the first quarter of 2021, VC companies continue to pump money into biotech.
The main trend worth noting in biotech investment is that early-stage investors seem to see the potential for significant breakthroughs, as stated by McKinsey, in how drugs are discovered, targeted, and delivered.
Biotechs with cutting-edge platform technologies have benefitted the most from investor interest.
For example, from 2019 to 2021, VC companies invested more than $52bn in therapeutic-based biotech companies globally, two-thirds of which went to start-ups with platform technologies.
Let’s take a look at the areas garnering the most investor interest.
Many biotechs and pharmaceutical companies are starting to leverage blockchain technology to make supply chains more traceable.
Given how complex supply chains can be due to the factors involved, such as the fact they span multiple continents and frequently have blind spots, it is unsurprising why blockchain technology is an area of interest for the purposes of increasing efficiency.
Being able to pinpoint gaps in the supply chain is a huge advantage for biotechs because it means that businesses can see all activity across the supply chain, including stakeholder activity.
This data offers the opportunity to provide a decentralised server on a network that can be accessed at all times, that is also secure and inalterable, minimising security and tampering risks.
Though blockchain technology is still in its early stages of adoption in the biotech and pharma industries, owing to the difficulties of scalability and costs in running blockchain nodes, it is likely to increase in interest over time.
After all, supply chain issues were rampant during the pandemic, so finding a digital solution is highly attractive to biotechs.
To put things into perspective, widespread adoption of blockchain could add $3bn worth of value to life sciences companies by 2025, and around 70% of life sciences leaders intend to set up a blockchain network in the next decade.
We’ve spoken about the impact of artificial intelligence in previous blog posts, but it continues to climb higher on the agenda of biotechs due to its vast array of potential applications.
From data analysis to drug trial outcome predictions, AI is changing operational efficiency in the biotech industry.
Predictive analysis using AI could even foresee market demand for specific medicines and aid in the discovery of compounds with strong therapeutic potential.
Gene editing is an area applying the use of AI that has garnered significant investor interest over the years, with the total value of VC deals in the area since 2012 reaching over $3.2bn(with over $1.3bn raised in 2021 alone).
Switzerland-based global healthcare company Novartis has been an early investor in gene editing technology, with four VC deals between 2014 and 2016, even creating guidelines for using AI ethically in medicine.
In this guide, Novartis describes the application of AI across the business, including:
Innovating R&D to develop novel therapies and drugs
Optimising business processes, operations and commercial activities
Engaging with patients, healthcare professionals and partners
This is described as being part of Novartis’ digital transformation to ‘embed cutting-edge digital technologies and data science into all parts of its business’.
In many ways, machine learning (ML) is the natural counterpart to AI, as both can work in tandem to analyse huge amounts of data that can streamline R&D processes and provide a handful of solutions based on thousands of potential scenarios.
Data is central to the biotech and pharma industries – from clinical trials, diagnostics and genomics, to drugs, therapies and wearables, data is a prominent currency in biotechnology.
ML has the potential to assist in areas of interest such as microbiome treatments, to help understand the microbiota’s genes and how they influence the body.
To do so relies on recognising patterns, which includes looking at significant amounts of data and factors to personalise potential treatments.
Precision medicine, a market valued at $65.89bn in 2021 and expected to reach a value of $146.57bn by 2028, is another area in which ML can enhance processes.
Using real-world data (data not from clinical trials), ML allows for a greater understanding of human health and disease on a patient-specific level.
Wearables – devices attached to patients that can collect individual data – can help with patient monitoring and trial participants across the world in real time.
Crucially, wearables can also be used to predict the risk of or diagnose major health conditions.
Deloitte Global predicts that 440 million units of consumer health and wellness wearable devices will ship worldwide by 2024.
Big data is a significant element of wearables, alongside the use of AI and ML, as the data from wearables can be harnessed to transform the diagnostic process.
As the use of wearables increases and technology advances, wearables could become an important predictor of health and even help researchers to observe patients during remote clinical trials, expanding the geographic regions in which researchers can operate.
As a market projected to be worth over $27bn by 2022, interest, investment, and growth will only increase in the next few years.
Will the biotech industry continue to evolve digitally?
If the last few years are anything to go by, digital transformation will continue to impact the way in which biotechs operate and innovate for the better.
As more businesses adopt transformative technologies, the potential applications will increase and adapt to the needs of the biotech industry and society.
In other words, digital transformation will continue to change the future of biotech, and investor interest will continue to be guided by the direction of these changes and their successes.
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