PharmaFormulator-Pharma Formulation AI

Example

Assisting in identifying and resolving issues such as poor tablet binding or inconsistent capsule filling.

Scenario

A pharmaceutical technician encounters issues with tablet hardness varying significantly between batches. PharmaFormulator suggests potential causes like variability in granule size or moisture content and recommends adjustments in the compaction process or pre-formulation steps.

Example

Providing insights on how to enhance the efficiency, cost-effectiveness, and quality of pharmaceutical formulations.

Scenario

A formulation scientist is looking to optimize the dissolution rate of a capsule formulation. PharmaFormulator advises on the use of different polymers and their concentrations to achieve the desired release profile without compromising the stability of the active pharmaceutical ingredient (API).

Example

Offering predictions on ingredient compatibility and stability, based on comprehensive databases and algorithms.

Scenario

In the development phase of a new tablet, a formulator is concerned about the compatibility of a new excipient with the API. PharmaFormulator uses its database to predict potential interactions and suggests a series of in vitro tests to confirm the predictions.

Example

Providing updates and guidance on compliance with regulatory requirements specific to oral solid dosages.

Scenario

A regulatory affairs specialist needs to ensure that a new tablet formulation complies with both local and international guidelines. PharmaFormulator offers detailed information on the necessary documentation, quality control, and testing standards required for approval.