If technologies such as artificial intelligence (AI), cloud computing and molecular computers are implemented correctly, pharma will usher in a new era of quicker, cheaper and more effective drug discovery and production.
With pharma largely preoccupied by the surge of research activity around drug discovery and vaccines due to the Covid-19 pandemic, Pharma IQ focuses in on three areas of technology that can help position pharma businesses for growth now and in future.
Here are the three areas of technology that can help a pharma business:
- AI and Machine Learning
- Cloud Computing
- Molecular Computers
Now let us take a look at each of these technologies and how they can help pharma companies in the future.
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AI and machine learning is changing drug discovery
We cannot talk about digital trends in biotech without first covering AI and machine learning. Since the emergence of these algorithm technologies in life sciences, there has been much excitement surrounding their use in expanding the scope and scale of drug research and improving process efficiency of manufacturing.
In drug development, AI has the potential to improve the 12 per cent approval rate of a drug from regulatory authorities and reduce the average US$2.6bn price tag for developing a single pharmaceutical product. This is due to the technology’s ability to use computer vision and analyze existing patient data to simulate chemical interactions and predict behavior based on genomics at a faster pace.
AI can also perform quality control measures, shorten design time, reduce material waste and improve production reuse, making the manufacturing process of developing a drug far more efficient. An article on the trending role of AI in pharma, highlighted that: “AI machine learning algorithms can not only ensure [manufacturing] tasks are performed very precisely, but also analyze the [production] process to find areas where it can be streamlined. This results in less material waste, faster production and more consistently meeting the product’s Critical Quality Attributes.”
For real-word examples of how AI is changing the pharma field, Christos Varsakelis, Team Lead AI/ML at The Janssen Pharmaceutical Companies of Johnson & Johnson and Mathew Divine, Senior Data Scientist at Boehringer Ingelheim, will be speaking at SmartLab Digital 2021, where they will argue the case for automation and augmentation, and reveal how pharma stands to profit from AI innovation.
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The evolution of cloud computing is enhancing innovation in pharma
Pharma’s regulatory bodies are changing how they approach innovation initiatives due to the emergence of cloud computing, which has made it possible to centralize data, and ensure data security and data sovereignty. Pharma firms are utilizing the cloud to store, analyze and handle larger volumes of information without having to purchase expensive computer hardware. This is providing manufacturers, scientists and pharma professionals with the means to monitor product performance and ensure product quality, which is facilitating the pursuit of innovation in tech.
Girish Malhotra, president at pharma administration solutions provider EPCOT International, argues that innovation must come from inside the product manufacturing organizations.
“Competitive pressures keep companies on their toes for product quality and safety through manufacturing process technology innovations and continuous improvements,” Malhotra asserts.
Cloud computing is reducing the time-expense of innovating biotech, with early-stage biotech startups through to the established big players utilizing the cloud as a tool for limiting operating expenses and allocating resources to new projects.
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Molecular computers are advancing the future of medicine
The same basic tools that allow computers to function are now being used to control life on a molecular level. A team of biochemists at the University of Washington (UW) School of Medicine created artificial proteins that function inside human cells by turning genes on and off, which aims to improve the safety and durability of future cell-based therapies.
David Baker, professor of biochemistry at the UW School of Medicine and director of the Institute for Protein Design, says this technological development will advance the future of medicine.
“Bioengineers have made logic gates out of DNA, RNA and modified natural proteins before, but these are far from ideal,” Baker states. “Our logic gates built from de novo designed proteins are more modular and versatile, and can be used in a wide range of biomedical applications.”
Molecular machines also have the capacity to drive the future of personalized and precision medicine with Zibo Chen, a recent UW graduate student and lead author to UW’s protein logic gates project.
Chen notes: “Longer-lived T cells that are better programmed for each patient would mean more effective personalized medicine treatment.”
To advance data-driven approaches in biotech and create long-lasting scientific value, find out how to unleash the full power of data in pharma labs with industry analysis from Pharma IQ and an exclusive case study from Merck.