N-SIDE launches Production App to optimise clinical manufacturing process

The software consulting company claims its software solution has already saved one pharma company €10.5 million

The company said that with clinical trial supply chains being notoriously difficult to manage due to constantly changing information and large uncertainty in clinical trial demand, multiple teams and siloed data, the new software solution can solve these challenges by considering "all the manufacturing constraints specific to each clinical manufacturing program to deliver the optimal plan and budget."

According to N-SIDE, the app automatically optimizes the usage of production assets and resources to reduce waste, budget and timelines and then facilitates communication of any changes to all stakeholders, worldwide.

"What-if scenario planning allows teams to understand how individual changes might affect the overall situation and proactively model different scenarios to design the optimal plan," N-SIDE said. "With readily available, accurate data, managers can make informed decisions and rapidly adapt to ever-changing clinical plans."

Explaining the app's capability, the company's Life Sciences Director Sébastien Coppe said the app "connects the dots between the strategic vision and the operational decisions for planning your clinical program manufacturing."

N-SIDE said its app has already been tested by a large pharmaceutical company to optimize the clinical trials manufacturing plan for a key biological compound, resulting in an 11% decrease -- or €10.5-million -- in manufacturing costs.

The company added that with ever-changing supply needs and long manufacturing lead times, it is extremely difficult for clinical managers to plan manufacturing to meet these highly variable needs while also minimizing waste, controlling costs and reducing the risk of disrupted drug supply.

"At a program level, this is particularly challenging as multiple trials need to be considered in different global locations, often with a lack of standardization in ways of working and out-of-date or unreliable data on which to base decisions," N-SIDE said.