Attachment No. 5 SOW.pdf

Attachment No: 5– Statement of Work

4. Statement of Work

Advanced Product Characterization and Artificial Intelligence Analysis

Background

The Division of Product Quality conducts research to advance the adoption of emerging technology for pharmaceutical manufacturing and development of generics of complex drug product. To this end, DPQR is seeking contractual service for non-invasive high-resolution imaging and Artificial Intelligence image analysis to characterize freeze-dried pharmaceuticals, and complex drug products to understand the impact of advanced manufacturing techniques, formulation, and process parameters on product quality and performance

Objective

To seek a contract service for non-invasive high-resolution image and AI analysis of pharmaceutical products, measure and simulate physical and microstructural parameters, correlate measured and simulated parameters with product performance, and process parameters.

Required Features

The required features and qualifications of the service provider are:

• Shall have a demonstrated record in microstructural analysis of complex pharmaceutical products

• Shall correlate the microstructure of pharmaceutical products with formulation, process, and product performance

• Shall acquire high resolution (0.6um) and low resolution (4um) x-ray microscopy images of pharmaceutical products non-invasively.

• Shall generate three-dimensional high-resolution images at 0.5um – 4um resolution

• Shall segment and generated high resolution segmented images with artificial intelligence

• Shall conduct image based computation of physical properties and 3 dimensional image-based modeling

• Shall qualitatively and semi-quantitatively measure the distribution of components of complex drug products

• Shall qualitatively and quantitatively characterize the microstructure, air-voids, porosity, surface area and solid wall thickness of freeze-dried products

• Shall simulate the effective diffusivity, corresponding mass flow rate and dry layer resistance of the process employed in manufacturing the freeze-dried products

• Shall measure or simulate the radial and axial spatial distribution of solids of the freeze-dried products and applicable complex dosage forms

• Shall generate qualitative and quantitative data on the drug migration from the drug loaded core to the blank membrane as a function of time of a polymeric disk.

• Shall characterize the microstructure and drug distribution of polymeric disk

• Shall simulate drug release from polymeric disk,

• Shall characterize the microstructure of pharmaceutical implants and eye inserts

• Shall conduct drug release simulations for implants and eye inserts

• Shall develop a correlation and directional analysis between simulated drug release and in vitro release testing

• Shall study or support the determination of the potential release mechanism of implants

• Shall develop appropriate method and acquire low- and high-resolution images of topical foam products

• Shall analyze low and high resolution images of topical product supplied to vendor

• Shall characterize the microstructure of topical products

• Shall have prior experience and peer reviewed publication in the field of advance imaging and Artificial intelligence analysis on pharmaceutical products

Deliverables

The deliverables shall include:

1. 3 Dimensional XRM imaging at 0.5μm - 20μm resolution

2. AI-based segmentation

3. Porosity and pore size distributions

4. Porosity and 3 dimensional spatial distribution uniformity

5. Solid phase (include but not limited to API) characterization: phase separation (if any),domain size (if phase-separated), thickness, and 3D spatial distribution uniformity

6. 3D simulation model built from the segmented image datasets

7. Transport properties such as effective diffusivity, and capillary pressure

8. Release predictions

9. Dry layer resistance and mass flow simulations

10. Reporting including high quality images and 3D movies

The deliverables should be delivered electronically to the below address:

ATTN: Maxwell Korang-Yeboah maxwell.korang-yeboah@fda.hhs.gov