Leveraging IoT for Efficient Drug Scale-Up in Pharmaceuticals: A Case Study of Dr. Reddy’s
Applicable Industries
- Life Sciences
- Pharmaceuticals
Applicable Functions
- Logistics & Transportation
- Product Research & Development
Use Cases
- Last Mile Delivery
About The Customer
Dr. Reddy’s is a NYSE listed company that manufactures and markets APIs, Finished Dosages, and Biologics in over 100 countries worldwide. As a vertically integrated global pharmaceutical company, Dr. Reddy’s has proven research capabilities, including a promising drug discovery pipeline and presence across the pharmaceutical value chain. The company has expertise in scaling up complex products from lab to the plant scale with an array of modeling tools. Process experts in the company help in reducing the scale-up risks from lab to the plant.
The Challenge
The pharmaceutical industry is fraught with numerous challenges, from drug delivery to equipment design optimization and scale-up problems. Increasing raw material costs and the unavailability of the right raw materials at the right time pose significant issues in meeting stringent product delivery deadlines. Dr. Reddy’s, a global pharmaceutical company, faced these challenges and sought to explore engineering simulations to address them effectively. The company engaged with ANSYS to leverage their expertise in this field, aiming to develop accurate scale-up conditions by performing steady-state and transient simulations at each scale. They sought to study parameters like velocity distributions, mixing times, and species concentrations from one scale to the other.
The Solution
ANSYS consultants used simulations to help Dr. Reddy’s understand the differences in micro-, meso-, and macro-mixing times from lab scale to plant scale. They also identified the risks involved in the scale-up at each particular rpm level and the formation of dead zones in plant scale simulations. Furthermore, they studied the evolution of individual species concentration and mixing performance using transient simulations. This consultation with ANSYS on engineering simulations provided valuable insights into the physics of scale-up and identified the risks involved. It guided Dr. Reddy’s in lowering the risk of scale-up batches and helped make better-informed decisions where minimal experimental data existed or where experimental data was difficult to obtain.
Operational Impact
Quantitative Benefit
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