Excited to share our second paper on #quantum machine learning out now in Science Advances! 🎉 Here we developed a model to predict neoantigen immunogenicity using a quantum convolutional neural network. #AI #immunology #immunology #quantum
science.org/doi/10.1126/scia…
Tyler Alban retweeted
📢 🎉 Excited to share our new @ScienceAdvances paper on quantum computing for HLA immunogenic peptide prediction and neoantigen discovery. ⚛️🧬
A great collaboration at the intersection of #QuantumComputing, #AI, and #CancerResearch.
📄 Paper: science.org/doi/10.1126/scia…
Tyler Alban retweeted
Excited to share our new preprint with @ClevelandClinic + @IBMResearch
We used AI + physics-based design to engineer TCRs targeting cancer neoantigens with:
✔ Mutant specificity
✔ Functional activation
🔗 biorxiv.org/content/10.64898…
#Immunotherapy #Cancer
Excited to share our new preprint with @ClevelandClinic + @IBMResearch
We used AI + physics-based design to engineer TCRs targeting cancer neoantigens with:
✔ Mutant specificity
✔ Functional activation
🔗 biorxiv.org/content/10.64898…
#Immunotherapy #Cancer
Tyler Alban retweeted
🥳🎆 Kicking of 2026 with our work showing intra-tumoral bacteria 🦠 affect outcomes of Radiotherapy + anti-PD-L1 now out in @NatureCancer with sister paper by @nataliesilvermd! Even when trials "fail" – we can learn from them! nature.com/articles/s43018-0…. -- w/ @GeneCollector, @imrtlee, @TylerAlban1, @DrHaddadRobert, the Pfizer team and more! (1/N)
Tyler Alban retweeted
Two papers in @NatureCancer highlighting the role of intratumoral bacteria & associated immune architecture (e.g., neutrophil influx) in mediating resistance to immunotherapy in head & neck cancer.
nature.com/articles/s43018-0…
nature.com/articles/s43018-0…
@GeneCollector @xrtGenomics
Tyler Alban retweeted
Tumor bacterial burden dictates immunotherapy fate in head & neck cancer (Preview @dspakowicz)
nature.com/articles/s43018-0… @NatureCancer
@GeneCollector @ClevelandClinic @imrtlee @MSKCancerCenter @xrtGenomics @pfizer @TylerAlban1 @DrHaddadRobert @DanaFarber
nature.com/articles/s43018-0…
Excited to highlight our recent work in bladder cancer using single cell RNAseq to identify a novel subset of CD6 positive T-cells that associate with BCG resistance. Great collaboration with Angela Ting and Byron Lee!
nature.com/articles/s41698-0…
It was a pleasure to present our teams work on AI designed T cell receptors at #ACS2025 ! Really exciting work coming out of the @ClevelandClinic @IBMResearch #discoveryaccelerator and the @GeneCollector lab!
Check out our new preprint! Here we optimized a #quantum #neuralnetwork for neoantigen prediction and demonstrated advancement in immunogenicity prediction and patient stratification based on predicted neoantigen load.
biorxiv.org/content/10.1101/…
Excited to share our manuscript on quantum machine learning! I’m a believer in team science so here we teamed up with quantum computing experts from @IBMResearch and used quantum ensemble approaches for modeling transcriptomic data to predict IO response.
arxiv.org/abs/2506.02213
Incredible opportunity to share the stage tonight with @VamsiVelcheti tonight at an amazing venue #ASCO2025 @CLEImmunoUpdate
Here at #ASCO2025 excited to give a talk later on our AI work! @CLEImmunoUpdate
Tyler Alban retweeted
At the National Academy of Medicine — Joined by my dear buddies and comrades in arms against cancer! Congrats!! @wolchokj @JenWargoMD Luis Diaz
Super cool to see our work highlighted by @ACIR_org If you haven’t had a chance to check it out yet this is a great summary!
New insights into nivolumab-induced immunoediting bit.ly/403lMIZ @TylerAlban1 @xrtGenomics @GeneCollector
Tyler Alban retweeted
New insights into nivolumab-induced immunoediting bit.ly/403lMIZ @TylerAlban1 @xrtGenomics @GeneCollector
We get all the cool tech in @GeneCollector lab! Excited to see how label free live cell sorting helps improve our single cell seq data quality! 🧐 @levitasbio
Tyler Alban retweeted
Excited to be part of team science published today in @NatureMedicine with @TylerAlban1 🗞️
Both NSCLC responders and non-responders had anti-tumor T cells. Responders target clonal antigens.
👉rdcu.be/dVyiU




















