AI and big data are set to be integral to the trajectory of the healthcare industry, identified by industry professionals as being one of the top technologies that will transform and adapt pharmaceutical drug discovery and development processes.
How exactly is technology advancing the pharmaceutical sector, and which areas are advancing the most?
The urgency resulting from the pandemic has meant nearly every industry has had to embrace technology advances more than ever.
Combined with increased regulatory hurdles and increasing R&D costs, pharmaceutical companies are having to adapt their business models to keep up.
One example of the rapid pace of development in the industry is the development of mRNA vaccines, which would have been impossible years ago due to the lack of technology necessary to create it.
Primarily, technology is being seen as a resource for the pharmaceutical sector to improve, adapt, and innovate.
This has led to many pharmaceutical companies re-thinking their digital strategies – 30% of companies in 2020 were creating digital strategies (up from 26% in 2019).
Big data – data in larger, more complex sets that cannot be processed by traditional data processing software – is being utilised more by pharmaceutical companies.
More than 30% of global healthcare industry professionals were currently using big data/analytics in their marketing and sales processes and expected to use it in the next two years.
Additionally, 28% of companies will be using big data/analytics to optimise drug discovery and development processes.
In such a data-driven industry, there is a need to advance processes to match the increasing volume and complexity of the data that is being generated, which is why big data is increasing in use.
With so much data being generated from a variety of sources, the priority for many pharmaceutical companies is organising and streamlining information.
Belgian startup Pryml has developed a platform allowing data scientists to build applications on sensitive data of organisations, creating a synthetic version of the confidential data and therefore enabling the restricted sharing of this data with third-party companies for research collaborations or business applications – just one example of data being used as a predictive model for drug recommendations.
Investors from the healthcare and pharmaceutical domain have previously invested around $4.7bn in big data analytics, which is likely to increase considerably.
Big data is shaping the way that pharma companies analyse their data to gain insights from it, whether historical or real-time data, offering the opportunity to identify hidden patterns to make data-driven decisions for the company.
According to McKinsey Global Institute, the application of big data strategies can optimise innovation, improve the efficiency of research and clinical trials, and build new tools for physicians, consumers, insurers and regulators to meet the promise of more individualised approaches.
All in all, big data is extremely beneficial to R&D costs, clinical trial processes, drug discovery, and even areas such as sales and marketing.
Artificial Intelligence (AI) has been a trending topic in the pharmaceutical sector for some time, and the list of potential uses for AI in pharma has only increased in time.
23% of healthcare industry professionals confirmed that their companies were using AI to enhance drug discovery and development processes, with 28% expecting to continue to implement or start using this technology in the next two years.
For pharmaceutical companies, AI offers the opportunity to rapidly accelerate R&D timelines, which in turn will have a knock-on impact on drug development costs and efficiency.
Unsurprisingly, many organisations see this as integral to the future of pharma – 62% of healthcare organisations are considering investing in AI in the future.
The likes of Roche, Pfizer, AstraZeneca, and Johnson & Johnson have already collaborated with or acquired AI technologies to great success.
Roche, for example, partnered with Owkin (a machine learning platform for medical research) to speed up drug discovery, development, and clinical trials.
AI is accelerating the speed with which pharmaceutical companies can discover new treatments and techniques, and with such a variety of potential applications, it is likely that AI will continue to positively impact the sector at large.
Additionally, the efficiency of vaccine technologies has also enhanced discovery and development process, particularly in Switzerland, where technologies such as mRNA, used for immune-oncology treatments, have been brought to light as a result of the pandemic, putting Switzerland at the forefront for vaccine innovation.
Changing market dynamics have led to the sector exploring new ways of manufacturing using technology, such as small batches for precision medicine.
Conventional bioreactors, for example, have a high turnaround time between batches, requiring cleaning and sterilisation after every run.
Single-use assembling, by comparison, offers ready-to-use sterile systems that are more efficient and cost-effective.
Single-use bioreactors are gaining traction for this very reason, as they considerably reduce downtime and positively impact productivity.
Most importantly, developments such as the use of single-use bioreactors offer more flexibility due to low energy needs and minimal waste.
An example is Scottish startup Cellexcus, which makes single-use airlift bioreactor systems, using patented technology using bubbles instead of mechanical mixing to move cells and nutrients – this single-use system can be used for a variety of cell cultures and fermentation.
The technology and uses above have been in development for some time, accelerated by the pandemic and the technology available to pharmaceutical companies.
Other areas, such as 3D printing, are still in the early stages and could be set to rise in popularity.
As 3D printing rises in popularity, there have been discussions around its application for printed organs using bioprinters, which could be used for transplants, with many speculating that this may develop considerably in the next five years, though this would be dependent on the speed and availability of printed organs.
In the US, 3D bioprinting is central to newer ways of testing pharmaceuticals, with US-based startup Frontier Bio offering ‘FLUX-1’, a 3D bioprinter for making human tissues, employing an electro-hydrodynamic printing technique. However, as mentioned above, 3D printing may take a few more years to become widespread in the sector.
In silico trials – experiments conducted via computer simulation – are rising in popularity, as a time-saving and cost-effective alternative to in vivo clinical testing.
In September 2020, Germany began reimbursing the first prescription digital health applications, with a total of 10 being reimbursed for use in conditions such as tinnitus, insomnia, anxiety and obesity – this has increased the number of digital health applications in Germany, though the uptake of digital health apps may be slower elsewhere.
However, given that these trials are yet to simulate the accuracy of clinical trials, in silico trials are likely to need further adaptation and evolution to be a significant contributor to technological advancements in pharma.
Technology advancements aren’t just helping the pharmaceutical sector, but instead, are shaping the future of it.
Using technology such as AI and big data offer the opportunity to truly gain insights from data and enhance drug discovery and development processes, which is more cost-effective and efficient in the long term.
With up-and-coming technology such as 3D printing being applied to the sector, pharma will only continue to innovate and break new ground.
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