Using Digital Tools In Process Development

By Dr. Alexander Krauland and Hermann Schuchnigg

Biopharmaceutical production has always been a challenging and time-consuming process. Traditional optimization methods focus on improving each step individually, but this can miss how those steps work together – slowing down the entire manufacturing process.

At Boehringer Ingelheim, we’re taking a smarter approach. By using integrated process models, machine learning and genetic algorithms, we’ve found a way to make production faster and more efficient. These models, powered by advanced algorithms, have already delivered results. For example, when applied to solubilization and refolding operations, these data-driven models predicted a twofold productivity increase. Expanding the models to include capture chromatography boosted productivity by 50 to 100 percent, depending on the baseline process.

This breakthrough shows how technology can transform the entire biopharma production process chain – not just one step at a time. It’s about finding smarter ways to bring biological medicines to life.