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Talk 1 |
Robert Docherty From Molecule to Materials to Medicine. A Celebration of 15 years of the Crystal Form Consortium (CFC). Accelerating the Development Journey Through the Application of Structural Sciences
The selection of the solid form for development is a key milestone in the conversion of a new chemical entity into a drug product. An understanding of the solid-state chemistry, crystallisation process and associated material attributes is crucial to help organisations convert molecules into materials and medicines. In this presentation we will reflect on the emergence of Pharmaceutical Materials Sciences over past two decades and the focus on the structural aspects catalysed by the Crystal Form Consortium. The Pharmaceutical industry continues to evolve, drug discovery is being transformed by an unprecedented understanding of disease, identification of new targets and disease pathways enabled through the application of digital tools. The impact of this change on the design, development and launch of future medicines will be significant. Shortened development times, reduced attrition, increased number of projects and diversity of dosage forms developed will increase the scientific challenge across the pharmaceutical sciences community. As we celebrate 15 years of the stewardship of the Crystal Form Consortium and look forward to the next decade we explore a digital design-based molecule to medicine journey. At the heart of this new digital tapestry, we re-imagine a crystallographic data thread that weaves together data sciences, computational tools, and current experimental practices as foundational elements of a strategy for the accelerated development and manufacture of advanced pharmaceutical products. |
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Talk 2 |
Suzanna Ward, CCDC The CFC and the CSD: How has the CSD evolved and what can the CFC expect next? |
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Talk 3 |
Simon Black, SyCryst How to Curate Morphological Data?
There is a shortage of high-quality morphological data for organic crystals. A largely untapped wealth of such data for over 2000 organic crystals is available in the work of P. Groth, which is freely available on-line. This talk explores the challenges and opportunities in comparing historical and more recent morphological data, highlighting the potential significance of the “morphology.cif". |
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Talk 4 |
David Lowe, Ian Bruno, CCDC Collection and Organization of Crystallization Data
The CSD is a comprehensive resource for structural information about organic and organometallic chemicals, but the knowledge it contains can be further enhanced by additional properties and context. Here we describe the results of a project to capture detailed crystallization conditions for a selection of 1600 entries from the CSD Drug subset, while also improving coverage of melting points and bioactivities, and beginning to record solubilities. Dealing with the practicalities of handling the crystallisation data helped us to create an ontology to define key parameters of the crystallization process, and this was then used to create a Knowledge Graph to enable the new data to be correlated with existing data across CSD entries and their chemical components. We will present the outcomes of this project to get input from CFC members on how we can best build on these going forward. |
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Talk 5 |
Matteo Salvalagio, UCL Rational Reduction of Computationally Predicted Crystal Energy Landscapes with Molecular Dynamics
Crystal Structure Prediction (CSP) methods should ideally identify the operative conditions to obtain a specific polymorph starting only from the molecular structure of their building blocks. Unfortunately, even if CSP methods have dramatically evolved over the past decade, the field is still far from achieving this vision. While successful predictions of the most stable polymorphs of organic crystals based on accurate lattice (free) energy estimates are becoming increasingly common, the number of predicted putative polymorphs remains a standing issue. Typically, the overall number of potential structures computationally identified as putative polymorphs usually grossly exceeds the number of polymorphs observed experimentally [1]. This problem in the field is typically referred to as "overprediction". A significant reason for CSP methods over-predicting possible polymorphs is that temperature increases molecular motions so that some structures that appear as distinct lattice energy minima merge into the same free energy minimum at finite temperature [2]. This work discusses applying a physics-driven computational procedure [3,4] to reduce the number of relevant local minima of crystal energy landscapes based on a systematic and scalable application of molecular dynamics and enhanced sampling simulations. To identify persistent crystal structures, we perform classical molecular dynamics simulations at finite temperature on CSP-generated crystal structures. Unstable configurations are then automatically removed by comparing the distribution of internal orientations against the random arrangement typical of a disordered melted state. To identify crystal structures that convert to a common finite-temperature state, we conduct a clustering analysis based on probabilistic fingerprints that capture information on the relative position, orientation, and conformation of molecules within a dynamic crystal supercell. Differences in the probabilistic fingerprints define a dissimilarity metric between finite-temperature structures, which is then used to perform unsupervised clustering of finite-temperature structures. In this contribution, we discuss the application of this method to systems of increasing size and complexity (urea, succinic acid, ibuprofen, olanzapine and others), spanning from a few dozen to thousands of structures. We note that, in all cases, we substantially reduce the crystal energy landscapes while consistently retaining the experimentally observed crystal structures. Moreover, we discuss how the results of this reduction feed into the development of systematic approaches to investigate potential kinetic bottlenecks to the observation of putative polymorphs [5,6]. Developing a Python library [7] that manages the setup of MD simulations and automatically analyses the resulting trajectories has been instrumental in achieving scalability over a large set of crystal structures, enabling us to apply MD workflows to sets of crystal structures approaching the size and complexity of real-world CSP applications. References [1] DA Bardwell, CS Adjiman, YA Arnautova, E Bartashevich, SXM Boerrigter, et al., 2011, Acta Cryst. B 67:535-55, [2] Price SL. 2013, Acta Cryst. B. 69:313-28, [3] Francia, N.F., Price, L.S., Nyman, J., Price, S.L. and Salvalaglio, M., 2020. Crystal Growth & Design, 20(10), pp.6847-6862. [4] Francia, N.F., Price, L.S. and Salvalaglio, M., 2021, CrystEngComm, 23(33), pp.5575-5584. [5] FM Dietrich, XR Advincula, G Gobbo, MA Bellucci, M Salvalaglio, 2023 Journal of Chemical Theory and Computation [6] AR Finney, M Salvalaglio, 2024, Wiley Interdisciplinary Reviews: Computational Molecular Science, e1697. [5] https://github.com/mme-ucl/pypol |
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Talk 6 |
Erin Johnson, Dalhousie University Quantitative Matching of Crystal Structures to Experimental Powder Diffractograms Identifying whether two experimental crystal structures determined under different experimental conditions correspond to the same polymorph is a challenging problem in crystallography, with practical (and even legal) implications. We recently developed a new quantitative metric for comparison of powder X-ray diffractograms (PXRD), termed the variable-cell powder difference. (VC-PWDF) method. VC-PWDF substantially improves the agreement with COMPACK compared to other PXRD-based comparison tools and is recommended to be used in conjunction with COMPACK to improve reliability of structure comparison. We further extended VC-PWDF to allow direct comparison of both experimental and in-silico-generated crystal structures to collected powder diffractograms. The resulting VC-xPWDF method correctly identified the most similar crystal structure to both moderate and “low” quality experimental powder diffractograms for a set of 7 representative organic compounds. This approach should allow for rapid identification of new polymorphs from solid-form screening studies by matching to a set of candidates resulting from crystal structure prediction, without requiring single-crystal analysis. |
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Talk 7 |
Grahame Woollam, Novartis Applied Molecular Modelling in the Pharmaceutical Industry The presentation will cover the application of molecular modelling tools within the pharmaceutical industry. Specifically addressing crystal polymorphism since structural changes can result in large differences in targeted properties applicable to both performance and safety. First-principles crystal structure prediction (CSP) gives us the possibility to identify stable polymorphs given only a molecular structure. Validation and value demonstration of modelling and experimental processes, provides opportunities to harvest novel crystal forms. It will be discussed how to influence resources and timing by informing on the risk associated with the form in hand; advising when it is safe to close exploratory screening activities, otherwise, intensify the search of a more stable crystal form. |
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Talk 8 |
Cheryl Doherty, GSK Insights from Proprietary Structural Databases |
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Talk 9 |
Helen Blade, AstraZeneca How AstraZeneca uses Crystal Structure Models to Risk-assess our Molecules
This talk will outline the ‘so what’ of using crystal structures in the pharmaceutical industry. It will talk through how the use of crystal structures and interrogation of structural features, lays the foundation blocks for developing compounds and ultimately launching drugs to the market. An outline will be given to show how industrial scientists use multiple applications and approaches to build up an understanding of the solid form. It will then show how this improved understanding is used to impact manufacturing processes, crystallisation development, formulation design, particle design, setting of storage conditions, supporting regulatory submissions, manufacturability of the drug substance and drug product, and ultimately the development control strategies. A number of case studies will be shown at various stages of development to show how crystal structures are becoming crucial to drug development. |
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Talk 10 |
Shubham Sharma, Pfizer Tales of Multi-polymorphic Systems through CSP & Informatics |
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Talk 11 |
Pietro Sacchi, CCDC Crystal Size and Shape effects in Polymorphism – a Modelling Perspective
Mechanochemistry in the context of molecular polymorphism allows to rapidly explore unique conditions for the formation of new phases using limited amounts of material. If applied in the early stages of research, this technique has the potential to identify potential processing bottlenecks derived from unwanted or unforeseen polymorphism. We demonstrated this for the infamous Ritonavir, where milling of form I for only 15 minutes using small amounts of solvent, allowed to isolate the stable form II. In addition, we showed how this transformation can be reversed, returning to the more soluble polymorph, albeit with considerably longer milling times. In this talk, I will present our results, focusing on the modelling of nanosized crystal particles and on the impact that the creation of exposed surfaces has on their stability. |
