Digital Transformation of the Drug Manufacturing Process

Know how Modeling And Simulation Lower Costs And Time To Market, Reduce Environmental Footprint, And Maintain Quality And Safety For Patients

Key Highlights

  • Pharmaceuticals can take over a decade to develop and cost billions 1 of dollars to produce
  • The scaling up of drug manufacturing processes contributes to the cost and delays at the very last stage when the product is ready to generate business.
  • Inefficient upstream and downstream manufacturing processes and packaging activities can further delay time to market, costing companies market exclusivity and limiting potential revenue.
  • Optimizing scaling up the manufacturing processes with modeling and simulation accelerates timelines without compromising quality, advances equipment performance, and reduces waste throughout the process.

Drug Manufacturers Endure High Costs and Long Delays

Bringing new pharmaceuticals to market is a slow, laborious, and costly process. Studies show that a single drug or vaccine may take 10 to 15 years and up to $2.5 billion to formulate, study, test, and produce — and just one in eight drugs receives regulatory approval. As the COVID-19 pandemic made clear, these timelines, costs, and low approval rates are unsustainable. For companies, it means lost revenue and wasted time, but for patients, it could be a matter of life or death.
For today’s pharmaceutical companies, the drug manufacturing and packaging processes contribute to the high cost and slow pace of getting a product to market.

Scaling up production, refinement, and packaging from lab- to industrial-level while maintaining patient safety, product quality, and sustainability efforts is a significant challenge. The traditional method of trial and error may work in other industries, but in pharmaceuticals, conditions must be exact or companies risk wasting expensive product. Pharmaceutical companies with less efficient manufacturing processes leave patients in need, limit revenue potential, reduce their market opportunity, and increase waste.

Modeling and Simulation Simplify Scaling Up

Drug manufacturing begins in earnest once the medication receives regulatory approval. At that point, the company must scale lab- or pilot-level production up to plant-level manufacturing while ensuring consistency throughout the upstream and downstream processes. But scaling up is not merely a matter of multiplying dimensions and ingredient volumes to match the expected market demand.To scale manufacturing effectively, stakeholders must understand precisely how the transition will affect the final product and calculate the adjustments required to increase output with no loss of quality or efficacy.

Traditionally, companies scale up manufacturing by iterating on potential setups, equipment, and processes until they find a solution that ensures effective production without deteriorating the active pharmaceutical ingredient (API). But this traditional approach requires numerous time-intensive physical iterations: manufacture the equipment, test a production line, measure the quality, and repeat until the desired quality is met.

In contrast, modeling and simulation enable pharmaceutical companies to actually see the flow in the mixing tank, the biological reaction in the bioreactor, or the coating process for each tablet. Then they can optimize manufacturing parameters, ensure stable product quality regardless of production variability, and minimize waste, all without the need for extensive physical experimentation.

Challenges in Scaling Up Drug Manufacturing

The downstream manufacturing process primarily involves purification
and formulation.

The benefits start with the purification process, during which filtration, chromatography, spray drying, and granulation equipment work in concert to extract a drug’s API. This equipment must be finely tuned to manage the complex physics of the purification process. Without a clear understanding of how their equipment will perform, however, companies are left to struggle through the same drawn-out, costly cycle of manual iteration. Modeling and simulation eliminate that struggle by enabling companies to quickly optimize purification
equipment designs and processes to ensure consistent results.

The formulation process — wherein a drug’s API is combined with other ingredients to create a safe, effective dosage form — is similarly complex. The powder mixing, coating, extrusion, and lyophilization processes must result in a uniform product, which means the equipment that executes them must maintain consistency across millions of units. Achieving that kind of accuracy in a timely, cost effective fashion simply isn’t possible without insights from modeling and simulation. With those insights in hand, pharmaceutical companies can optimize equipment performance in much less time at a much lower cost, which both eliminates significant amounts of energy and material waste and ensures that the ten millionth tablet is indistinguishable from the first.

Simulation Drives Successful Digital Transformation

With the right tools, pharmaceutical companies can swiftly scale from lab to industrial production while reducing costs and delays, delivering both immediate and long-term benefits.

Design optimization

Traditional scaling to plant-level manufacturing is time-consuming and costly, involving multiple physical prototypes and tests. Modeling and simulation accelerate the process, allowing rapid virtual iterations and design validation before physical implementation.

 

 

Enhanced Troubleshooting

Modeling and simulation accelerate troubleshooting at every stage of drug manufacturing. Issues with equipment design, prototypes, or production processes can be identified in hours instead of days. This allows stakeholders to resolve problems early, preventing impacts on product quality, rising costs, or unnecessary delays.

 

 

Creating a Digital Twin

Modeling and simulation help pharmaceutical companies build digital twins by capturing data on equipment, product chemistry, and process efficiency. These twins provide insights to enhance manufacturing, reduce costs, boost quality, and minimize waste. Simulation data also supports AI integration, enabling faster or automated processes while retaining valuable institutional knowledge.

 

Summary and Recommendations

Drug production often takes over a decade and costs billions. To meet global healthcare demands, pharmaceutical companies must adopt modeling and simulation to reduce costs, streamline scaling, and accelerate time-to-market. Sticking to traditional methods risks delays, lost market share, and financial setbacks. Embracing these technologies ensures efficiency and competitiveness.

  • Assess the organization’s scale-up processes, including the design and fine-tuning of mixing tanks, bioreactors, spray dryer, and other essential equipment, to gain a clear understanding of the time and cost involved.
  • Identify the impact that accelerating drug manufacturing by 50% would have on costs and product release timelines.
  • Determine how modeling and simulation can improve the organization’s drug manufacturing outcomes and adopt solutions that meet its needs