DIGITAL ASSISTANT TO SUPPORT PRODUCT DEVELOPMENT

In order to facilitate product development, such as pharmaceutical product development, a computer implemented method and an apparatus are proposed that enable formulators to develop robust drug formulations in a cost- and time-efficient manner. To start the development process, the user selects the preferred dosage form (e.g., granules, pellets, capsules, tablets etc.), defines a target profile (e.g., amount of active ingredient per unit, size of dosage form, mechanical strength of dosage form, desired release behaviour etc.) and enters key characteristics of the active ingredient (e.g., true density, particle size distribution data, bulk and tapped density, angle of repose, compressibility and compactibility profile etc.). The identity (e.g., chemical name or structure) of the active ingredient is not necessarily disclosed. The apparatus processes the provided data and calculates key parameters of the AI (e.g., particle size, powder density, powder flow and tabletability). Similar key parameters are calculated for common pharmaceutical excipients and stored in the apparatus. The apparatus then selects all relevant excipients and suggests a suitable manufacturing process. Combinations of active ingredients and excipients qualify as drug formulation if the predicted properties comply with the defined target profile. The following aspects can be considered: solubility and permeability of the active ingredient, dissolution of the active ingredient, probability to pass the content uniformity criteria, flowability of the powder blend, tabletability of the powder blend, mechanical strength and size of the tablet, compatibility of active ingredients and excipients etc. Afin de faciliter le développement d'un produit, tel que la mise au point d'un produit pharmaceutique, un procédé mis en œuvre par ordinateur et un appareil sont proposés qui permettent à des formulateurs de mettre au point des formulations robustes de médicament d'une manière rentable et rapide. Pour démarrer le processus de mise au point, l'utilisateur sélectionne la forme galénique préférée (par exemple, des granulés, des pastilles, des capsules, des comprimés, etc.), définit un profil cible (par exemple, la quantité de principe actif par unité, la taille de la forme galénique, la résistance mécanique de la forme galénique, le comportement de libération souhaité, etc.), et entre des caractéristiques clés du principe actif (par exemple, la densité réelle, les données de répartition granulométriq