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Bee stinger catheter for directly injecting drugs into tumors

Hacker News

Bee stinger catheter for directly injecting drugs into tumors

When the immune system encounters a new antigen, it needs to make a decision about whether to attack, or to ignore. Making the correct decision is important for fighting infections, killing cancer cells, and avoiding autoimmune diseases. The decision is made using time-dependent chemical signals and computations that occur at different places (tumor, lymph node, blood). So if we think of the immune system as a computer that uses chemical signals, rather than electrical signals, how do we communicate with the immune system, to help it make the right decisions? My lab has designed a catheter that allows us to deliver time-dependent chemical signals into tumors and lymph nodes. The catheter contains a 3D printed retention mechanism to prevent migration, and it is implanted using image-guided, minimally invasive techniques. Different drugs can then be delivered into specific locations at specific times, using programmable pumps, to convince the immune system to attack cancer antigens.

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Product HuntOn track for Day 1 leaderboard · Strong signals: computer, new, using · Missing: mac, agents, macos
69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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