Viewpoints By Sachin Misra

Article: Future-Proof Your CPG Operations with Composable PLM

Composable PLM is an approach to managing the entire lifecycle of a product that emphasizes modularity, flexibility and adaptability. This solution leverages existing legacy PLM investments where upgrades or rip/replace are not feasible due to cost, timeline, complexity or organizational resistance.

Microblog: Automation Fair 2023: How Thermo Fisher Doubled 7-day OEE by Harnessing its Production Data

Thermo Fisher is using Digital Performance Management (DPM) and services from Kalypso to enhance real-time production visibility and accelerate performance improvement in its bio-pharmaceutical operations. Results include increased OEE and generating $5 million more in revenue from a single line.

Microblog: Life Sciences Industry Forum: Digital Transformation for an Evolving Industry 

During this year’s Rockwell Automation Automation Fair, Kalypso principial Sachin Misra was joined by other industry experts to discuss digital transformation within the life sciences industry.

Article: Unraveling the Complexity of Tech Transfer

If we have another pandemic, could we throw 300 people at tech transfer? Absolutely. But does that work for a commercial product? No. We need to think about the fact there are technologies available that can remove as much of the human element from tech transfer as possible.

Article: Digitally-Enabled Sustainability for Pharma

the pharmaceutical industry is held accountable for its sustainable products and operations. To meet this challenge, organizations need to consider the formulation complexity, product safety, quality and regulatory considerations that have been and will remain top of mind.

Article: Make Better and Faster Decisions with a Manufacturing Control Tower

A legacy of siloed functions in pharma and biotech organizations inhibits innovators from developing and commercializing therapies with speed and efficiency. Manufacturing organizations rarely have access to key insights and information from research and development (R&D), quality, supply chain, sourcing, procurement, and logistics functions and systems. This is particularly true for product and process data stored across enterprise applications. R&D professionals may use Digital Knowledge Management (DKM) systems to manage product and process data, including formulation and packaging information, but often this information is not easily accessible to the manufacturing organization that has to make daily production decisions based on available supply and capacity. Demand forecasting, sales and operations (S&OP) and supply planning functions may use purpose-built solutions and enterprise resource planning (ERP) systems to align demand, supply, capacity, sourcing events and purchase orders, but when they run into supply constraints or demand fluctuation, manufacturing cannot react quickly, preventing them from making proactive decisions on how to best meet production demand.

Article: Digital Knowledge Management: A Key Step on Pharma’s Journey to the Connected Enterprise

In March 2020, the Pharmaceuticals industry faced one of its most public-facing and time-pressing challenges to date: develop, manufacture, and distribute a vaccine for COVID-19 globally as quickly and safely as possible. While sheer human perseverance played a pivotal role in driving the notable speed to market for the vaccine, this approach is not sustainable nor practical for commercial drug products. Digital methods and tools should be leveraged to achieve similar results in a sustainable, efficient, and profitable way. Pharmaceutical manufacturers now face the need to confront these challenges head-on and embrace connectivity across the value chain, starting with laying the digital foundation for innovation in the form of Digital Knowledge Management and Pharma 4.0.

Article: AI in Pharma: Emerging Use Cases Across the Value Chain

The pharma industry’s product development processes is complex and lengthy, but digital technologies can help. Here are the top AI use cases.