Using AI and the pharma cloud to boost efficiencies as the complexity of medicines grows

by Kelly Doering, Sr Director, Industry Marketing, Pharma, AspenTech

Medicines are becoming ever more complex in response to growth in personalised treatments and the development of a wide range of therapeutics to address less common conditions or rare diseases.

Examples of the latter include small molecules linked to large, perhaps conjugated to a chemotoxic agent for targeted cancer treatment; peptides linked to peptides; oligos linked to molecules that allow for better cell permeability; and lipid-encapsulated molecules that prevent degradation. But it is the market for more personalised medications that is seeing particularly rapid growth. The global personalised medicine market size is expected to reach US$ 796.8 billion by 2028, having expanded at a compound annual growth rate (CAGR) of 6.2% from 2021 to 2028 according to a new report by Grand View Research, Inc.

That’s posing challenges for pharmaceuticals manufacturers. One obstacle is that there are a wider array of variables to measure and different instrumentation may be required to do it. With a variety of modalities, this can also require different manufacturing processes and production lines of 1-cell and gene therapies and personalized medicines often require dedicated sites or small, modular manufacturing spaces close to the patient.

Varied types of data also equates to more data. Seeing, analysing and understanding complex data from any location becomes very difficult – a challenge sometimes exacerbated by inherited doubts about the integrity of cloud data.

Finding a way forward

To address these challenges, forward-thinking pharmaceutical companies are realising they need to change and innovate to fix the issues they have. More and more such businesses are coming to the conclusion that in order to tackle their problems, it will be imperative to implement advances in cloud applications, AI and machine learning in their manufacturing processes and workflows.

These advanced technologies are increasingly prevalent in the pharmaceuticals space. The global AI in pharma market reached a value of nearly $699.3 million in 2020, having increased at a compound annual growth rate (CAGR) of 31.8 % since 2015. The market is expected to grow from $699.3 million in 2020 to $2,895.5 million in 2025 at a rate of 32.9%, according to  "AI In Pharma Global Market Opportunities and Strategies to 2030: COVID-19 Growth and Change." 

Embracing advanced, innovative new technologies like AI doesn’t have to be hugely disruptive. Pharmaceuticals manufacturers don’t have to change everything at once, and a steady step-by-step progression is typically best. Businesses in this space should prioritise where their pain points are and start slowly working to clearly-defined goals - but it is key to ‘just start’.

Manufacturers can get the ball rolling by conducting risk-based assessments of their current processes.  By putting real-time monitoring in place, they can streamline the data review process.

Perhaps most important of all, using AI and cloud solutions enables them to compile reports on drugs more quickly and efficiently to be sent for regulatory submission. This is one step that translates to getting medicines to market faster.

How digitalisation drives the supply chain

Once companies have followed this path, they multiply the gains of digitalisation. They benefit from a more efficient production cycle that ensures quality, automates time-consuming processes, reduces risks, removes unplanned downtime and prevents bottlenecks, and drives faster product release. And they reduce costs and further accelerate process optimisation by eliminating time-consuming manual ways of working.

Many of the benefits that are realized with the implementation of digital technologies in pharmaceutical manufacturing can extend to the supply chain. With increased data accessibility, supply chains become more transparent end-to-end, enabling companies to improve communications with partners and across sites to swiftly shift sourcing or production to meet changes in supplier capacity, quality or market demand.

Across these procedures, manufacturers can optimise quality through process design, monitoring and control, reducing downtime through predictive maintenance built on prescriptive analytics. By taking out ‘lost time’ from the manufacturing process that is needed before products are released, they can create a more reliable supply chain.

That enables manufacturers to effectively guarantee to the end customer that the product will be available on time and will be ready for distribution when it is needed. And that’s a huge benefit when it comes to delivering high volume medicines, in particular.

Enabling agility for manufacturing a wide array of medicines

Companies’ decision-making becomes more outcomes-driven as they model scenarios encompassing a huge range of factors. They can start by learning from their current operations and that’s powerful.

Having the agility to adjust operations based on outcomes gives pharma companies the ability to optimise facilities and maximise financial impact.

However, digital technologies also need to be about supporting the enhanced agility manufacturers need to deliver a wide array of medicines. If a company is agile, then they can accommodate both routine, high volume (large batch products as smaller batch lower volume products, not to mention different types of drugs – from solid dose and small molecule products to biologics. And this ability to support enhanced agility is another compelling example of how digitalisation can deliver a raft of benefits for pharmaceutical manufacturers today.