Artificial
Intelligence (AI) based formulation development is a promising tool for
streamlining the drug product development process. AI is a versatile approach
that contains multiple algorithms that can be applied in different
circumstances. Critical material attributes (CMAs) and processing parameters
(CPPs) can have an impact on a variety of product attributes during the product
development process, including dissolution rate, particle size distribution,
physical and chemical stabilities, and the dry powder aerosol performance.
There are different types of tablet defects such as capping, lamination.
Mottling, chipping, cracking, sticking, picking, double impression, etc., these
defects can be detected with AI tools such as Terahertz Pulsed Imaging (TPI),
Time resolved microtomography images, Acoustic microscopy, convolutional neural
network, Automated visual inspection, UV/ Vis imaging based PAT tool,
Multivariate image analysis, etc. However, the conventional trial and error
approach for product development is inefficacious, laborious and time consuming
therefore we can use the AI tools to overcome problems associated with
pharmaceutical dosage forms. This review gives the following visions: (1) a
general introduction of AI in the pharmaceutical science and principle guidance
from the regulatory agencies, (2) To detect tablet defect (3) data preparation
and processing, (4) insights on applications and case studies of AI as applied
to solid dosage forms. In addition, the innovative technique known as deep
learning based image analytics will be covered along with its pharmaceutical
applications. By using emerging AI technology, scientists and researchers can
better understand and analyse the properties of drug formulations to promote
more efficient drug product development processes.
