digital solutions in a pharma & biopharma space No deviation

Challenges of Implementing Digital Solutions in the Pharmaceutical & Biopharma Space

We have looked at digital transformation in the form of accelerating Quality 4.0 in the previous article. Now, we will take a look into some of the factors leading to this shift towards digitalization and some of the challenges in implementing digital solutions in the pharmaceutical and biopharma space.  

Pierre Kardasz (CPG/Life Sciences Industry Manager, Asia Pacific) and Kenny Tay (Life Sciences Industry Consultant, Southeast Asia) from Rockwell Automation gave their views on this topic during the ISPE Singapore Affiliate Conference & Exhibition 2022 and shared their experience on the challenges that companies faced during the implementation of digital solutions. 

global life sciences industry trends no deviation

Figure 1: Global life sciences industry trends  

Before we move on to the challenges of implementing digital solutions in the pharmaceutical and biopharma space, let’s look at what’s driving digitalization in this industry. Figure 1 shows some of the trends that are currently shaping the global life sciences industry and these play an important role in the digitalization of this industry.   

  • Shift to complex targeted biologics: More companies are moving on to more complex processes. This results in the requirement for increasingly complex quality control.  
  • Expedited drug approvals: The duration taken for drug approvals has shortened drastically. The time taken used to be around 5 to 8 years, but some can take around 7 to 12 months now. The speed of product transfer has to be improved. 
  • Personalized medicines: Personalized medicines are used in a way where medical decisions are tailored to individuals based on their predicted response or risk of disease. There is a move from providing multi-dose vaccines to single-dose vaccines, as well as moving from vials to prefilled syringes. There is an increasing need for more flexibility to be built into manufacturing.  
  • Workforce shortage: Due to the occurrence of Covid, the way in which the workforce performs its work has changed. Companies have also started looking into employing digital solutions to help out with the situation, e.g. using AI in manufacturing processes.  
  • Regulatory and price scrutiny: With increasing scrutiny from the public in terms of the cost of producing a drug, as well as from regulations, there is a need to use technology to improve operational efficiency, compliance and data integrity.  
  • Network security and counterfeiting: There are possibilities where hacking can occur, resulting in the loss of important data. Cyber and network securities are therefore important concerns.  

Although these trends mentioned above help the industry in moving towards digitalization, and though digital transformations can bring about various benefits, Pierre Kardasz shared that out of 8 Proofs of Concept in the life sciences industry, 75% of them fail to scale. This is attributed to the fact that digital transformation projects are often very complicated to implement.  

Why is it difficult to implement a digital transformation project? Because when it comes to implementing digital solutions in a pharmaceutical and biopharma space, first, there is a need to understand the stage of digitalization that your plant is currently at, as well as to identify the digital theme that your project falls under and the benefits that can be derived from the project. Only with this understanding can a proper plan then be put forward to the relevant stakeholders to achieve a good business outcome. Some of the benefits that can be derived include an increase in output and productivity, cost reduction, time-to-market reduction, waste reduction etc. 

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Figure 2: Digital Plant Maturity Model and the different stages that a company can achieve  

Now that we know there is a need to understand the stage of digitalization a plant is at, let’s take a look at the different stages of a digital plant. According to the Digital Plant Maturity Model, as shown in Figure 2 above, there are 5 different stages that a company can go through.   

Stage 1 (Pre-Digital): Everything is paper-based and manual.   

Stage 2 (Digital Silos): Data and equipment are in a silo state and not connected, they have local batch recipes.  

Stage 3 (Connected Plant): Plant has ERP (Enterprise Resource Planning), and Manufacturing Execution Systems (MES). Rockwell sees that more than 70% of Southeast Asian companies (Pharmaceuticals and Biotech) are moving towards a connected plant.  

Stage 4 (Predictive Plant): This stage is achieved when there is supply chain visibility and integration of R&D into the manufacturing stages.  

Stage 5 (Adaptive Plant): There is full integration from supplier to patient, and zero system downtime. There is also a predictive and prescriptive kind of maintenance mode.   

key digital themes that underpin a typical life sciences process no deviation

Figure 3: 12 key digital themes that underpin a typical life sciences process  

In addition to understanding the stage of digitalization, we have also mentioned earlier about the need to know the digital theme that the project falls under. With the years of accumulated experience in this field, Kenny shared that Rockwell has identified 12 digital themes that will affect the profitability and productivity of a company in the life sciences industry. How a company goes about executing a digital transformation project in 1 of these 12 themes is thus very crucial. The 12 themes, which are shown in Figure 3, are as follows:  

  1. Production planning: The increasing need to use digital tools to provide a forecast for complex production plans and cater for any kind of contingency plans when required.  
  2. Optimization for critical processes: Process optimization for critical processes related to Critical Process Parameters (CPP) and Critical to Quality (CTQ) parameters to help reduce the number of deviations related to the process.  
  3. Throughput/Yield optimization: By using data analysis tools, model predictive control, artificial intelligence (AI) or machine learning kind of model, use cases can be obtained on critical processes, such as bioreactors or chromatography. These allow companies to study batches where there are higher yields, and thus improve their chances of yield optimization.  
  4. Quality management: As we go digital, paperless quality management systems can better address data integrity issues, while allowing for track and trace. It also improves productivity to some extent, as virtual audits on these paperless systems can also be conducted.  
  5. Information solutions & emerging technologies: Dashboards and machine connectivity digital twins use real-time data to allow monitoring of process performance. The digital twin, which is a virtual replica, allows for different scenarios to be tested on a system and thus allows process issues to be predicted before they even happen, resulting in optimization opportunities.   
  6. IT/OT convergence: IT systems are integrated with Operational Technology (OT) systems to allow for secure data flow and real-time actionable data transactions between the equipment and systems.  
  7. Predictive and remote maintenance/monitoring: Companies used to have preventive maintenance. But with analytics for conditions monitoring, predictive maintenance can be achieved, as machine health is now better monitored.  
  8. Labour productivity: With the use of AR and VR, operators can be trained more easily and efficiently without even needing to be onsite. AR and VR can help mimic the process, and operators can learn at their own pace.  
  9. Intelligent energy management (PEMS): While more companies are going green, not many are keeping track of their utility consumption. Intelligent energy management helps to solve this issue.  
  10. Production logistics: Automated storage and movement serialization allows for optimal use of the production storage space and allows for ease of tracking of the materials within that area.  
  11. & 12. Safety & security management: Machine safety solutions, as well as security solutions, are used to protect the plant and the operators.  

benefits of pharma 4.0 no deviation

Figure 4: Benefits of Pharma 4.0  

When a digital transformation project is well understood and implemented, there are various benefits that may be derived, as shown in Figure 4 above. Here we are using the implementation of an Electronic Batch Record (EBR) in a plant as an example to discuss the derived benefits.  

An EBR helps to simplify the batch record review process by allowing for review by exception. The batch record review process can be reduced to just hours compared to the many days taken when paper batch records are being reviewed. This increases the productivity of the personnel performing the batch record review. With a shorter turnaround time for batch record review, the batch release is also now much quicker, and this reduces the drug product time to market. With more batches being able to be released to the market, the cost of producing a quality drug product will also be reduced.   

When undertaking a digitalization project, it is therefore important to know the stage of digitalization your plant is in, and the digital theme that you are targeting to bring about the improvements.  

At No deviation, we have extensive experience in executing and implementing digitalization projects in the form of the Kneat paperless validation software, the Plant Quest critical asset management software, and the Mirrhia Environmental Monitoring System (EMS) & Contamination Control software for pharmaceutical and biopharmaceutical companies. If you would like to discuss digital solutions in a pharmaceutical and biopharma space or have any questions regarding the same, please contact us at  

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