Explore survival and event data for the REGAL Phase 3 trial with adjustable assumptions.
Compare a Phase 2 drug candidate's results against historical trial data using simulations.
Estimate a range of possible company valuations based on sales projections and approval odds.
Share a specific scenario with someone else using a single generated link.
| sterno874/sls-model | 00kaku/gallery-slider-block | 3rd-eden/ircb.io | |
|---|---|---|---|
| Stars | 0 | — | — |
| Language | JavaScript | JavaScript | JavaScript |
| Last pushed | — | 2021-05-19 | 2016-11-16 |
| Maintenance | — | Dormant | Dormant |
| Setup difficulty | easy | easy | easy |
| Complexity | 2/5 | 2/5 | 2/5 |
| Audience | researcher | general | developer |
Figures from each repo's GitHub metadata at analysis time.
No installation needed beyond serving static files locally, the Vercel deploy step is optional.
This repository is an interactive model for tracking and analyzing SELLAS Life Sciences, a biotech company known by its stock ticker SLS. The project builds a web based tool that lets people explore the company's clinical trial data, drug pipeline, and possible valuation scenarios using publicly available and primary sourced information. It is explicitly not investment, medical, legal, or financial advice. Instead it shows a range of possible outcomes and how sensitive those outcomes are to different assumptions. The tool is organized into tabs. One tab focuses on a Phase 3 clinical trial called REGAL, showing survival data, statistical sensitivity checks, and a way to compare different scenarios using shareable links. Another tab models a Phase 2 drug candidate, comparing its results against historical data with simulations. A third tab estimates the company's potential value by combining sales projections, approval probability, and a simulation of possible outcomes. A fourth tab explains all of this at different levels of detail, from very simple to highly technical, with sources linked throughout. Every adjustable number in the model is marked so users can see exactly which inputs are assumptions and which are confirmed facts with a citation. The statistical methods used, such as survival analysis and event tracking common in clinical trial research, are documented inside the app itself, with references to the academic papers they come from. Technically, this is a plain website built with HTML, CSS, and JavaScript using ES modules, with no build tools or npm dependencies required to run it locally. A small serverless function fetches live stock quotes when deployed on Vercel. The entire state of a scenario, including every slider and setting, can be encoded into a shareable web link with no server or database needed to store it. There is also an embed mode for showing a simplified version of the tool inside another webpage. The code includes automated tests that check the underlying math stays accurate over time. The project is licensed under AGPL v3.
An interactive web tool that models clinical trial data, drug pipeline progress, and possible valuation scenarios for the biotech company SELLAS Life Sciences, for research and education only.
Mainly JavaScript. The stack also includes JavaScript, HTML, CSS.
Copyleft license requiring that any modified version distributed or run over a network also be released as open source under AGPL.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Don't trust strangers blindly. Verify against the repo.