Jungkyu Park

A member of technical staff at @Ataraxis_AI

[Jungkyu Park @jpatrickpark]

Neoadjuvant therapy means months of treatment before surgery. Knowing a patient's chance of pathological complete response (pCR) before treatment could help tailor that treatment.

Today we're releasing two preprints on NEO, our AI model that predicts a patient's chance of pCR from a routine biopsy slide. 🧵

[Jungkyu Park @jpatrickpark]

@Ataraxis_AI @dhruva_biswas @joecappadona @JanWitowski @kjgeras Preprint on NEO: https://t.co/j31VyPr1UR
Evaluation in PHERGain and PHERGain-2: https://t.co/z4BDwHTgV0
Blog post with interactive figures: https://t.co/AKlZFNa9iM

Please share with anyone interested in AI, cancer research, or the future of cancer care!

[Jungkyu Park @jpatrickpark]

Neoadjuvant therapy means months of treatment before surgery. Knowing a patient's chance of pathological complete response (pCR) before treatment could help tailor that treatment.

Today we're releasing two preprints on NEO, our AI model that predicts a patient's chance of pCR from a routine biopsy slide. 🧵

[Jungkyu Park @jpatrickpark]

The work was done at @Ataraxis_AI by myself, @dhruva_biswas, @joecappadona, Cerise Tang, Ken Zeng, Bartosz Machura, Chuwen Liu, @JanWitowski, and @kjgeras, with our scientific advisor Rich Caruana (Intelligible).

Huge thanks to @dhruva_biswas for helping make this work much stronger and for all the writing and refining we did together.

We also had support from multiple collaborators: @PTarantinoMD (Dana-Farber), @Omene_CO (Rutgers Cancer Institute), Francisco Esteva (Northwell), Rohit Bhargava (UPMC Magee-Womens), Marcin Braun, Kamila Paździerz, Jakub Czerwiński and Hanna Romańska-Knight (Medical University of Łódź), @AlbertGrinshpun, Bareket Daniel and Michele Buchinger (Shaare Zedek), @fredhow (UChicago), Piotr Wysocki (Jagiellonian University), Brie Chun (Fred Hutch), and Freya Schnabel (NYU Langone).

The evaluation in PHERGain and PHERGain-2 was completed with @wearemedsir and our clinical collaborators, including @JavierCortesMD, Antonio Llombart-Cussac, Jose Manuel Pérez-García, Manuel Ruiz Borrego, Peter Schmid, and Marco Colleoni.

[Ken Zeng @KenZeng56288846]

My thoughts after listening to your talk today @kchonyc

[Jan Witowski @JanWitowski]

We've recently developed new causal AI methods that allow us to simulate patient outcomes under counterfactual treatment scenarios

Importantly, as we start to scale these world models, they begin to generalize zero-shot to multiple solid tumors - incredible work by our team:

[Ataraxis AI @Ataraxis_AI]

Today, Ataraxis is announcing a new generation of AI models that learn to predict treatment response and patient outcomes, and generalize zero-shot from breast cancer to multiple solid tumors.

Blog post: https://t.co/yfzHsf6UCU

[Krzysztof Geras @kjgeras]

How aggressive a cancer is and how large is the benefit from chemotherapy are different estimands. Genomic assays were built decades ago for the first and repurposed for the second.

Today, we released 3 preprints on estimating the benefit of escalated treatment directly.

[Krzysztof Geras @kjgeras]

What if a routine breast cancer H&E slide could help answer a hard question: how likely is this cancer to come back? Our @NatureComms paper introduces a multimodal AI test for recurrence risk across invasive breast cancer subtypes.

https://t.co/ilqvEYFwbT

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[Krzysztof Geras @kjgeras]

We are looking for exceptional candidates for technical roles at @Ataraxis_AI:
* Research Engineer (Optimization/Systems): https://t.co/OXkC1cu2zs
* Research Engineer (Data Science): https://t.co/S73fzW66eQ
* Research Scientist (Causality): https://t.co/fqDEcx86em

Join us!

[Ataraxis AI @Ataraxis_AI]

Today, we announce a strategic research collaboration between Ataraxis AI and MEDSIR (@wearemedsir), a global leader in oncology research.

The partnership will evaluate the Ataraxis Breast platform in several international randomized controlled trials. Together, we aim to generate robust clinical evidence on the role of artificial intelligence in predicting outcomes and treatment effects in early-stage and metastatic breast cancer. The analyses will especially focus on novel therapies investigated in MEDSIR's groundbreaking trials, including CDK4/6 inhibitors and antibody-drug conjugates (ADCs).

This is one of many ongoing partnerships at Ataraxis working on developing a robust evidence base supporting the accuracy and utility of Ataraxis AI-native tools, and moving AI precision oncology closer to becoming the standard of care.

Read the full announcement here: https://t.co/vFAG0BYhrn