BAGIM is an active community of Boston area scientists bringing together people from diverse fields of modeling and informatics to impact life and health sciences. BAGIM strives to create a forum for great scientific discussions covering a wide range of topics including data management, visualization, computational chemistry, drug discovery, protein structure, molecular modeling, structure-based drug design, data mining, software tools, and the sharing of goals and experiences. Our community is made up of participants from academia, government, and industry whose goal is to engage in the discussion of science involving a synthesis of theory and technology. Discussions sponsored by BAGIM are targeted to the needs and interests of informatics scientists, computational chemists, medicinal chemists, and statisticians. BAGIM also provides opportunities for networking within these disciplines as well as an arena for the dissemination of information of specific interest to the membership.

Saturday, February 18, 2023

Enric Herrero - Exploring the Exa-space with 3D-based screening methods

We are happy to announce our speaker, Enric Herrero, presenting Exploring the Exa-space with 3D-based screening methods

Please join us for a in-person event

Date: Thursday, March 23, 2023 at 6:00 PM

Sign-up: BAGIM Meetup

Title:  Exploring the Exa-space with 3D-based screening methods


Many huge commercial libraries have appeared in the last 5 years that include Billions of molecules with a reasonable synthesizability and represent a huge opportunity for the drug discovery ecosystem. Bigger libraries can increase the chances of finding interesting hits in a drug discovery project but also represent a challenge to process with existing in-silico methods.

Several approaches have been proposed to deal with these chemical spaces that use simple molecule representations to contain the computational and storage cost. However, 3D representations add valuable binding information of the ligands and representations that are heavily tied to the chemical structure tend to limit the chemical diversity of the proposed solutions.

In this talk we are going to discuss how to tackle the problem of exploring huge chemical spaces in the Exa-scale without sacrificing the advantages of 3D based methods. Different approaches will be presented and compared in order to see the advantages and disadvantages of different molecule representations and screening methods and create a debate around the topic.

Saturday, February 11, 2023

Soumya Raychaudhuri: Using genetics & genomics to define mechanisms autoimmunity

We are happy to announce our latest speaker Soumya Raychaudhuri, Professor of Medicine and Biomedical Informatics, Harvard Medical School, https://immunogenomics.hms.harvard.edu/

Please join us for a virtual event on

Date: April 12, 2023

Time: noon ET / 9 am PT

Sign-up: BAGIM Meetup

Title: Using genetics and genomics to define mechanisms of autoimmunity

Abstract: To be confirmed

About the speaker:

Dr. Soumya Raychaudhuri is an Associate Professor at Harvard Medical School and at Brigham and Women’s Hospital. He is also appointed as an Associate Member at the Broad Institute and a Visiting Professor in Genetics at the University of Manchester. He matriculated into the Stanford University NIH funded MST program in 1997 after completing degrees in mathematics and biophysics at the University at Buffalo. In 2004, he completed both his medical training and his doctoral training in biomedical informatics. After completing his clinical training in Internal Medicine, he joined the rheumatology fellowship training program in 2006, and concurrently completed his postdoctoral fellowship training under Mark Daly at the Broad Institute. Since starting his own group in 2010 at Harvard Medical School and Brigham and Women’s Hospital, his lab has focused on finding and fine-mapping disease alleles and understanding their significance in immune-mediated diseases. He has focused on multiple diseases including rheumatoid arthritis, type I diabetes, and tuberculosis infection. He has worked on fine-mapping HLA loci, devising integrative statistical genetics strategies to identify causal variation by taking advantage of largescale epigenetic data, and integrating genetic data with functional genomics and data on human immunological phenotypes.

Saturday, February 4, 2023

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

We will be planning a September BAGIM in-person event with XtalPi. Registration to open on Wednesday, August 16, 2023

Michael Bellucci - Reducing Risk in Crystallization Process Development, Wed, Sep 13, 2023, 5:30 PM | Meetup

Date: September 13, 2023

Location: TBD (Cambridge, MA)

Attendance: 70 (maximum)

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.

Wednesday, February 1, 2023

Eric Sigel - Exploring Predictive Workflows in Small Molecule Discovery through DEL-ML

BAGIM is excited to announce our first in-person event of 2023. We are partnering with TandemAI on this event with invited speaker Eric Sigel.

Date: March 1, 2023

Time: Event time: 5:30 - 7:30PM - Talk promptly starts at 6 pm ET with Q&A immediately afterwards. Please arrive no later than 6 pm.

We will be serving complimentary drinks and refreshments.

Sign-up: BAGIM Meetup

Location: The Royal Sonesta, Riverfront Room - East Tower, Level 2, 40 Edwin Land Blvd., Cambridge, MA 02142

TitleExploring Predictive Workflows in Small Molecule Discovery through DEL-ML

AbstractAI/ML has rapidly moved from being a curiosity to center stage across the biotech industry. Novel approaches are being enabled by these new methods and the increasing ability to generate the large-scale data needed to drive the technology. However, the impact of these rapid advances is limited by an industry that is only beginning to adapt to the new paradigm. The presentation will use DEL-ML (Machine Learning on DNA Encoded Library data) to explore the predictive workflow including results of its application, needed shifts in the small molecule discovery mindset, and directions where the technology can move from here.