Aishwarya Balajee - Keeping up with the Data Model

 We will be planning a September BAGIM in-person event with Zifo. We welcome Aishwarya Balajee with the presentation Keeping up with the Data Model.

Registration to open on Wednesday, August 30, 2023
Details of event will be posted in the next few weeks

Date: September 27, 2023
Location: CIC Cambridge, 245 Main St, Cambridge, MA
Mixer and Presentation: 5:30 PM - 7:00 PM
Welcome, Introductions, Presentation, Q&A, Conversation

Host: BAGIM & Zifo
Speaker: Aishwarya Balajee
Abstract:
The Science behind the drug discovery and development landscape has evolved over the past decades. Along with this, the data and technology ecosystem surrounding it has seen an evolution. From in-vitro to in-vivo to genomics to multiomics – Data has come a long way, aiding in important insight generation. The Data remains as the backbone and core to the research.

Take for example, a house - it is built following a blueprint, and this blueprint can be reused to build more such houses. In a laboratory scenario, when it comes to procedures or experiments, most scientists and research laboratories have their own set of protocols that are followed. When a process has a standard template/structure, why not the data that’s being generated? What is the equivalent of the blueprint in the data world? It is the data model.

If we want to answer questions of the future, we need to make our Data model adaptable to it. We often see Data consumers today, are running into challenges when trying to find data to answer questions that were once not anticipated – Data that is not collected, data that is collected but stored in inappropriate formats, data that is missing or not identifiable etc. While data producers are often racing against time trying to find that one molecule or target. In a quest to keep up with technological advances, data was captured at massive rates, but structure and governance surrounding it, was often overlooked mainly due to the ever-changing dynamic of said technologies. Futuristic data models have the responsibility now to be framed in a way they can stand the test of time allowing for inferences to be drawn from data, regardless of the technology.

In this talk, we want to discuss the topic of keeping up with the fundamental data model changes. We would like to discuss solutions to keep the underlying Data model “living and adaptable” to future questions we want the data to answer.

Speaker Bio

Head of Digital Services, Zifo, North America
With a background in Biomedical engineering, Aishwarya spent the last 10 + years enabling various Biopharma customers accelerate Science. She is passionate about solving challenges in the intersection of Science, Technology and Data. She currently heads the Digital Services division in North America, helping customers define Digital transformation strategy, Data architecture and enabling Lab data automation.

Michael Bellucci - Reducing Risk in Crystallization Process Development

 Date: September 13, 2023

Location: TBD (Cambridge, MA)

Attendance: 70

Mixer and Presentation: 5:30 PM - 7:00 PM
Welcome, Introductions, Presentation, Q&A, Conversation

Host: Dr. Sivakumar Sekharan, Senior Director Business Development

Speaker: Dr. Michael Bellucci, Senior Director, Solid Form Design

Abstract Title: Intelligent Cloud-Based Algorithms for Reducing Risk in Crystallization Process Development
Michael A. Bellucci*,1, Anke Marx*,2, Bing Wang1, Liwen Fang1, Yunfei Zhou1, Chandler Greenwell1, Zhuhong Li1, Dirk Wandschneider2, Jan Gerit Brandenburg2, Guangxu Sun1, Sivakumar Sekharan1, Axel Becker2

1 XtalPi, Inc., 245 Main Street, Cambridge, MA 02142
2 Merck KGaA, Frankfurter Str. 250, A022/001, 64293 Darmstadt, Germany

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.

Kyle Martin - In-silico antibody developability: Dynamic Profile Predictions

 We are happy to announce our latest event being sponsored with Discngine. We welcome Kyle Martin, Postdoctoral Fellow, Boehringer Ingelheim. This will be a in-person event.

Title: In-silico antibody developability: Embedding Dynamics in Intrinsic Physicochemical Profiles Prediction

Date: May 18, 2023
Time: Event time: 5:30 - 8:00PM - Talk promptly starts at 6 pm ET with Q&A immediately afterwards. Please arrive early.
Location: Residence Inn Boston Cambridge

Abstract: To bring an antibody-based medicine to the market, it needs to be stable, safe, and easy to manufacture. Following the concept of holistic in silico developability, Kyle Martin and colleagues have evaluated the molecular properties of antibody-based biotherapeutics in the market, including conformational flexibility of the Fvs using molecular dynamics (MD) simulations. In this event, you will learn how the Developability Navigator In Silico (DENIS) allows researchers to compare monoclonal antibody (mAb) candidates for their similarity with market-stage biotherapeutics in terms of physicochemical properties and conformational stability. This advanced computational tool promises to accelerate the progress of biotherapeutic drug candidates from discovery into early development by predicting drug properties in different aqueous environments.

Presenter: Kyle Martin, Postdoctoral Fellow, Boehringer Ingelheim

Bio: Dr. Martin got his PhD in biophysics from the University of Idaho in 2020 where his research ranged from predicting Ebola virus escape mutants to protein stability in the subsurface ocean of Saturn’s moon Titan. He started his postdoctoral research at Boehringer Ingelheim in 2020. His postdoctoral research has focused on antibody design via in-silico tools including molecular dynamics and predictive models. He’s published 2 papers as a co-author and 1 paper as a main author while at Boehringer.

Reference: https://pubs.acs.org/doi/10.1021/acs.molpharmaceut.2c00838