2) Physical Property Based Crystallization Process Dev Archives - Pharma Crystallization Summit

Dr. Jian Wang, J-Star Research

wpadm — Mon, 26 Sep 2022 22:43:49 +0000

Dr. Jian Wang is an expert in API crystallization, with comprehensive knowledge of the science and technologies required to meet the needs of small molecule drug development. She has over 30 years of R&D experience in API crystallization and reaction engineering, and has been providing R&D services since 2005 to pharmaceutical clients around the globe.

Dr. Wang received her Ph.D. degree in Chemical Engineering in 1994, from the University of Pittsburg with Prof. Donna Blackmond and Prof. Irving Winder. She published 20 peer-reviewed articles and 6 patents (5 related to API crystallization) before getting into technical services.

During her 11-year tenure at Merck since 1994, Jian became an expert in API process R&D and a champion in implementing science-based and technology-enabled approaches. She promoted the application of PAT tools in process R&D serving as a consultant at Mettler Toledo AutoChem during 2005-2010. In 2011-2013, Jian took the responsibility as VP of Crystallization Development at Crystal Pharmatech, helping a diverse client base in solving API crystallization problems. To better assist new drug development programs, Jian started up a state-of-the-art crystallization center at J-Star Research in the beginning of 2014 complementing its strong API Process Research. She now leads the Center for Pharma Crystallization at J-STAR as Senior Vice President, addressing a wide range of challenges associated with API isolation from early to late developmental stages. Working closely with drug formulation experts, Jian also has been driving the establishment of drug formulation services at J-Star that are well integrated with API crystallization R&D.

Session 2: Physical Property Based Crystallization Process Development

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Intelligent Cloud-Based Algorithms for Reducing Risk in Crystallization Process Development

wpadm — Sun, 17 Jul 2022 02:49:58 +0000

By Dr. Mike Bellucci, XtalPi Inc

Crystallization is the most widely used separation and purification process in the pharmaceutical industry. The resulting crystal structure and corresponding crystal morphology isolated from this process can have a profound influence on the physical properties and manufacturability of drug product APIs. Consequently, the ability to characterize the crystal polymorph landscape and control the crystal morphology are two fundamental aspects of pharmaceutical manufacturing. At XtalPi, we have developed a cloud-based computational platform that combines advanced physics-based algorithms with A.I/machine learning algorithms in order to mitigate polymorph risk and support rational design of crystallization experiments for improved morphological control. We highlight various applications from our Crystal Structure Prediction and Morphology platforms and discuss our recent investigation of the effect of polymer additives on the crystal growth of metformin HCl. This study was performed both with experiments and computational methods with the aim of developing a combined screening approach for crystal shape engineering. Additionally, we have developed analysis methods to characterize the morphology “landscape” and quantify the overall effect of solvent and additives on the predicted crystal habits. Further analysis of our molecular dynamics simulations was used to rationalize the effect of additives on the growth rate of specific crystal faces.

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A Digital Mechanistic Workflow for Predicting Solvent-Mediated Crystal Morphology

wpadm — Sun, 17 Jul 2022 02:44:40 +0000

By Prof. Kevin Roberts, University Of Leeds

The crystallization of organic materials provides a common, energy efficient methodology for the purification and isolation of high value compounds such as pharmaceuticals. The inherent anisotropic molecular and morphological properties of these materials can affect downstream ingredient processing such as powder flow, blending and compaction as well as impact upon product quality associated with stability and bioavailability. Hence, the ability to control the morphological characteristics of crystals through the rational design of the crystallization process can be important to reduce bottlenecks in both R&D and manufacturing associated with the production of new drug products.

In this presentation a digital mechanistically-based workflow, encompassing a combination of attachment energy and grid-based systematic search methods, is applied to predict the solvent-dependent morphologies of the monotropically related α and β polymorphic forms of L-glutamic acid. This work encompasses calculation of the crystal lattice energy and its constituent intermolecular synthons, their interaction energies, and their key role in understanding and predicting crystal morphology. It also assesses the surface chemistry, topology, and solvent binding on crystal habit growth surfaces. Through a comparison between the contrasting morphologies of the conformational polymorphs of L-glutamic acid, the overall approach highlights how the interfacial chemistry of organic crystalline materials and their inherent anisotropic interactions with their solvation environments direct their crystal habit with potential impact on their further downstream processing behaviour.

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Simulation aided solvent selection for robust impurity rejection by crystallization

wpadm — Sun, 17 Jul 2022 02:24:22 +0000

By Dr. Yuriy Abramov, Exe. Director of CC&DS, J-Star Research

Regulatory expectations for control of impurities in new drugs have been established through ICH guidelines. The most efficient approach to impurity rejection is provided by API crystallization. Computational applications are highly desirable to guide crystallization design for fast-paced projects.1 Novel impurity uptake computational model is proposed, which considers solvent, lattice-substitution and doping level contributions to impurity incorporation into crystal structure during crystallization. Application of the model for impurities rejection from various APIs, including investigational oncology drug candidate MRTX849, is presented.

1. Abramov, Y.A. Cryst. Growth Des. 2018, 18, 1208−1214.

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A new approach to stere-opure atropisomeric molecules enabled by continuous flow-crystallization

wpadm — Sun, 17 Jul 2022 02:17:21 +0000

By Dr. Michal Achmatowicz, Mirati Therapeutics

Abstract: A new approach to stereopure atropisomeric molecules is enabled by a continuous flow-crystallization process. Continuous accumulation of the product under its optimal crystallization conditions is combined with a parallel synthetic process occurring within its own optimal regime. Therefore, in a holistic sense, this approach constitutes an asymmetric synthesis via dynamic kinetic resolution (DKR). The application of Simultaneous Processing of Antagonistic Chemical Events methodology (SPACE-DKR) will be showcased on a densely functionalized active pharmaceutical ingredient (MRTX1719) for which significant yield improvement (from 37% to 87%) was realized.

This protocol provides a complementary means to atroposelectivity for substrates which challenge current asymmetric methodologies, and greatly improves sustainability by decreasing consumption of solvent and advanced synthetic intermediates

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