What You Will Learn

Please join Carterra and Absci at our upcoming symposium in Boston, MA. You will spend the day learning about high-throughput drug discovery with some of the industry’s leading scientists. Our speakers will present new ways of looking at discovery, applications, and workflows, including HT-SPR. The topics you'll hear about include:

Workflows enhancing the speed or efficiency of drug discovery
AI and ML initiatives and in silico antibody discovery programs
Small molecule applications: TPDs, DELs, PROTAC^®s, Membrane Proteins
Novel assay designs including HT-SPR applications
Emerging modalities such as next-gen antibodies: scFVs, nanobodies, bi-specifics, ADCs
Strategies to maximize impact in specific therapeutic areas such as immuno-oncology, infectious diseases, and neuroscience

Network with your peers. Lunch will be provided. Registration is required as seating is limited.

Companies presenting in 2024:

Agenda	Symposium Co-hosted by Absci
9:45am – 10:00am	Arrive and Check-in
10:00am – 10:30am	Networking and Coffee/Tea
10:30am – 10:45am	Symposium Begins—Welcome
10:45am – 11:15am	Philip Kim, PhD, Professor, Department of Molecular Genetics & Department of Computer Science, University of Toronto Machine Learning based methods for protein and peptide design
	Abstract: I will cover machine learning methods developed in my lab that cover protein sequence design, de novo protein design and antibody design, making use of graph neural networks and diffusion models. We also have developed methods to model the conformational dynamics of peptides using PepFlow, a sequence-conditioned boltzmann-generator model. We show that PepFlow achieves state-of-the-art performance for peptide structure prediction and matches experimental conformational ensembles.
11:15am – 11:45am	Nicholas Abuid, PhD, Field Application Scientist , Carterra Driving discovery of novel medicines using Carterra’s HT-SPR technology
	Abstract: Carterra’s LSA^® and LSA^XT platforms have changed the landscape of drug discovery. Across small and large molecule therapies as well as vaccines, the power of high throughput multiplexing and innovative assay configurations is enabling new strategies to tackle the “undruggable” space and discover novel medicines. This talk will emphasize areas where HT-SPR technology continues to push the boundaries of real-time, label-free binding. With HT-SPR, research workflows benefit from seamless data integrations and the necessary breadth and depth of data to deliver on the promises of AI/ML-based drug discovery.
11:45 – 1:00pm	Lunch and Networking
1:00pm – 1:30pm	Karanbir Pahil, PhD, Investigator, GSK High-throughput SPR in DNA-encoded library screening and hit validation
	Abstract: DNA-encoded libraries (DELs) enable drug discovery chemists to identify thousands of hits from screening campaigns using billions of molecules, producing a vast array of small molecule structure-activity relationship data and potentially interesting chemical matter that needs to be triaged efficiently. DELs are made combinatorically, with every library member being assigned a unique DNA barcode, and every step of chemistry being compatible with the presence of DNA. Here, we show how we leverage the facility of resynthesizing DEL screening hits with DNA tags and the Carterra LSA^® platform to enable high throughput binding assays.
1:30pm – 2:00pm	Mark Ibrahim, MS, Scientist, Merck Leveraging computational design, miniaturization, and microfluidics to accelerate the discovery and engineering of therapeutic proteins
	Abstract: Protein-protein interactions (PPI) are key regulators of physiology, and dysregulation of these interactions often cause disease states. Naturally, designing biotherapeutics to either disrupt or form PPIs is a common therapeutic strategy as demonstrated by many antibody-based therapies. To accelerate our discovery of biotherapeutic candidates, Discovery Biologics leverages novel computational design methods, miniaturized production platforms and microfluidic technologies with the capacity to measure thousands of PPIs in a single continuous experiment. Binding experiments at this scale combined with next-generation sequencing are being used with machine learning and statistical deconvolution to inform the design of new sequences with enhanced properties and specificity.
2:00pm – 2:30pm	David Eavarone, PhD, Associate Director, High-Throughput Screening, Absci Amir Shanehsazzadeh, Senior AI Scientist, Absci Generative AI powered by high-throughput screening for antibody design
	Abstract: Generative AI has the potential to improve the quality and speed of therapeutic antibody discovery. AI models require datasets of antibody-antigen interactions, consisting of paired complexes (sequence or structure) and labeled data. We demonstrate AI models succeeding on three antibody design tasks: structure design, structure-based sequence design, and sequence optimization. The first two tasks utilize generative models trained on antibody-antigen structures and are validated via HTS and SPR enabled by Carterra LSA^®. The latter task uses predictive models, trained on high-throughput affinity datasets, for multiparametric affinity maturation. These efforts highlight the powerful synergy between AI and HTS for antibody design.
2:30pm - 3:00pm	Networking and Refreshments
3:00pm	Symposium Ends

What You Will Learn

Register Here

Agenda