Lucent

Tokenized Life Sciences

[Lucent @UseLucentHQ]

@OrionLee43 @ax1vc I think part of it is helpful people understand the world of data out there (it's quite large in this space) -- but also helping folks understand that trading has it's own nuances / unpredictability, so we don't want to overpromise in terms of predicting price movement.

[Lucent @UseLucentHQ]

@dyorealm @ax1vc If you're using crypto for something like this, you basically need to abstract it away so it's not seen as a "crypto" thing

[Lucent @UseLucentHQ]

@ketuart02 @ax1vc @JulianMalinak You need to have a reliable way of organizing data and a well-trained AI. That said, users need to understand that nothing is guaranteed in trading / investing.

[Lucent @UseLucentHQ]

@ketuart02 @ax1vc @JulianMalinak Lots of clinical trial outcomes are somewhere between "smashing success" and "total failure", and there are lots of ways that mediocre results are spun to make them seem better than they actually are.

[Lucent @UseLucentHQ]

@VanquishSnake @ax1vc @JulianMalinak We think a lot of the value of what we're building works similarly for the hot areas like gene therapies or more obscure stuff that isn't "hot" from a narrative perspective. It's around understanding the corpus of data available and training AI to understand what's important.

[Lucent @UseLucentHQ]

@OrionLee43 @ax1vc The regulatory piece is definitely hard. We don't want to overpromise on the prediction front, but we're starting to train our AI using expert input on regulatory issues; the idea is to give the AI some intuition around what regulators might do.

[Lucent @UseLucentHQ]

@OrionLee43 @ax1vc A lot of it around training AI to understand the different types of spin that companies use to try to puff up trial results. The good news is given the amount of trials historically, you have a fairly robust dataset.

[Lucent @UseLucentHQ]

@Cherrypoppie7 @ax1vc @JulianMalinak It's definitely an area where you have to constantly be improving, part of what we're trying to do for example is having our AI get continually better at understanding the common types of spin that companies use to make trial readouts sound better than they are

[Lucent @UseLucentHQ]

@xaliora @ax1vc With that said, the challenge is that some useful information companies may want to hold close to the vest and not talk about (i.e. supply chain challenges). There are some expert sources we're looking to tap into, but it's definitely an area we want to work more on.

[Lucent @UseLucentHQ]

@xaliora @ax1vc That's a great question: so we track all public filings (and are adding other sources, like conference presentations etc) and our agents are constantly getting better at separating the signal from the noise.

[Lucent @UseLucentHQ]

@OrionLee43 @ax1vc With that said, the companies where I think intel is easier to gather are therapeutics companies developing specific drugs rather than AI companies (which are often selling tech to therapeutics companies).

[Lucent @UseLucentHQ]

@OrionLee43 @ax1vc One nice thing about biopharma is that the clinical catalysts are fairly clear: there are clinical trial stages with known endpoints, published results, etc. Public companies have to make filings as well.

[Lucent @UseLucentHQ]

@ax1vc thanks for taking the time, really enjoyed the convo! If you want to try the platform go to https://t.co/CUIAGR5jqv and fill out the form. We're looking for biopharma traders / investors, experienced or newbies! We would make it open but uses a decent amount of compute.

[AX1 @ax1vc]

X Space - Thursday, May 28, 5PM UTC

AX1 is partnering with @UseLucentHQ

Lucent is an Alliance alum building in one of the harder corners of investing: biopharma.

Join us with @JulianMalinak, co-founder of Lucent, to discuss why biopharma may need a much better investing interface.

This market moves on FDA decisions, trial readouts, filings, expert debates, and small signals most investors never learn how to read.

A lot of the information is technically public, but public does not mean understandable.

It is scattered and hard to turn into a view before the market already reacts.

Lucent is building for that gap.

AI-native biopharma intelligence that helps investors track catalysts, understand company and asset-level context, and see why a signal may matter.

Set a reminder.

https://t.co/eQtwcKxW4X

[AX1 @ax1vc]

X Space - Thursday, May 28, 5PM UTC

AX1 is partnering with @UseLucentHQ

Lucent is an Alliance alum building in one of the harder corners of investing: biopharma.

Join us with @JulianMalinak, co-founder of Lucent, to discuss why biopharma may need a much better investing interface.

This market moves on FDA decisions, trial readouts, filings, expert debates, and small signals most investors never learn how to read.

A lot of the information is technically public, but public does not mean understandable.

It is scattered and hard to turn into a view before the market already reacts.

Lucent is building for that gap.

AI-native biopharma intelligence that helps investors track catalysts, understand company and asset-level context, and see why a signal may matter.

Set a reminder.

https://t.co/eQtwcKxW4X

[Lucent @UseLucentHQ]

Stay tuned...