A drug substance’s physicochemical properties determine the critical attributes for successful development into a viable product. A strong understanding of the drug product and its manufacturing processes aids in identifying attributes, which must be controlled to reproducibly manufacture the desired product.
Additionally, the explosive growth of data technologies has opened the door to a vast landscape of inviting scientific inquiries. However, proper statistical techniques, such as predictive analytics, design of experiments, and machine learning, are necessary to distill data into meaningful action.
Quality by Design
The application of quality by design (QbD) in pharmaceutical product development is of paramount importance to the success of new drug development. Product development time, prompt regulatory approval, and reduced validation burden can be realized when QbD is successfully implemented. We understand the importance of providing sound scientific advice in the early stages of product development, and can help to identify critical design characteristics that ensure success.
Design of Experiment
Predictive modeling of chemical exposure is a critical component of effective environmental stewardship that protects the environment and the public health. However, ecosystems are very complex. Contamination is introduced over time and space in highly variable ways. Statistics have a major role in quantifying effects, assessing consequences, and providing evidence of relationships.
Analytical Methods Development
Whether your business is pharmaceuticals or device development, robust, accurate and precise analytical methods are essential for monitoring the final product quality. The methods are the analytical lenses through which scientists and engineers can view the quality of a product, and just like a lens, the better the method the easier it is to see the quality.