PAICON
Medical Practices
Health data from 60+ countries, harmonised into one foundation. Ask a question, build a cohort, license the dataset.
Is PAICON hiring?
As of November 5, 2026, PAICON has no open roles in the job sources Metaintro tracks.
Hiring pattern
How fast PAICON is adding roles, and how they're set up.
New roles each monthRoles first posted in the month
Customers
All 14 companies PAICON names as customers.
Customers hiring now2
- SRH46 open roles
- Genomics England5 open roles
Other customers12
- BioMed X, Co-founder, BioRN & HI-STEM
- Leg&airy, Technology Entrepreneur
- PharmaSearch Ltd, Molecular Biologist & Geneticist (Oncology)
- Mitra Bio, Former Director of AI/ML, AstraZeneca
- Pixel Scientia Labs, Digital Pathology Expert, Host, Impact AI Podcast
- Genome Canada, Physician-Scientist
- Queen Mary University of London
- Remaining 84
- ETICCS
- iXora Health
- iPath
- DKFZ
What their customers say
Quotes from people at PAICON's customers.
“The sad story is that doctors have learned to silently adjust. Especially in the Global South. They've learned to silently, in their own practices, behind doors, adapt reference ranges, adapt treatment norms, adapt dosages based on their own trial and error experience.”
“Most clinical trials, because it has always been done that way, are done with white, middle-aged subjects. These clinical trials are completely neglecting that a drug that works in a white, middle-aged man might not work in a woman in the Caribbean who is of African descent.”
“There needs to be a way to do basic research on those so-called rare diseases, create venues for researchers, positions, clinics, hospitals, universities, to find pathways for their research to get into translation. That could be through feeding a centralized database, which then could become an AI.”
“If you're not putting diverse data in AI, you're not going to get diverse outcomes, and this is where the last mile of AI fails. We have to start collecting the data from all those populations, not just from the subset of people that walk through the door in a clinical trial site.”
“We do not get adoption unless we have trust. We don't get trust unless we have understanding and explainability of these systems. And if we don't get adoption, we don't have impact. There is a chain of consequences we have to set up to get to actual clinical impact.”
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“Unless you take an equity-focused approach to genomics and the gathering of data, supported with the engagement of participants and with an awareness of ethical issues, you have data, but it has no value. You don't have anything if you don't do that.”
“Most AI models perform beautifully in the lab, but they frequently fail in the real world. That could be a biomarker that looks bulletproof on an internal test, but collapses in external trials, or a tumor classifier that breaks when applied to slides from a new scanner or staining protocol.”
“My own cancer test came back with a variant of unknown significance. What that really meant was: I'm Latina, I'm from Colombia, and my genome isn't represented in international databases. The science simply didn't know what my result meant.”
“PCSK9 inhibitors, a medication very effective in lowering bad cholesterol and preventing heart attacks, were found because some African ancestry individuals were included in a study. If those Africans were not included, today we would not have that medication. More people will have died. Maybe millions of people will have died.”
“One in every four Africans have adverse drug reactions to warfarin, the world's most prescribed anticoagulant. We already have algorithms that accurately predict overdose risk for Europeans. But if you are non-European, those algorithms don't work well.”
“Once you develop your algorithm on a certain amount of demographic population, your solution is working on that population. Once you go to another part of the world where you don't know the demographic of that region, your AI will definitely fail there.”
“We knew from the start that diversity is king. We would have to look at different ethnicities for sure, which are not represented usually in the clinical trials as well.”
“But what exists is already changing. Human biology was never static, and globalisation has only made that visible faster. The science is chasing a moving target, and that is not the problem. That is the point.”
AI launches and partners
What PAICON has launched and who it works with on AI.
- PartnerPAICON and Morphle Labs partnershipPAICON and Morphle Labs announced a partnership for integrated AI solutions in cancer diagnostics.
- ResearchLEOPARD ChallengeThe page describes an international benchmark of AI models predicting time to biochemical recurrence from H&E prostatectomy slides.
- OperationsAI agents for data qualityPAICON uses AI agents to continuously improve data quality in its datalake.
- PartnerPartnership with Morphle LabsPAICON and Morphle Labs announced a partnership involving integrated AI solutions for cancer diagnostics.
Skills they ask for
Most frequent across open postings.
Tech stack
- CDN
- cdnjs
- Cloudflare
- CMS
- HubSpot CMS
- Analytics
- Google Analytics 4
- Marketing
- HubSpot
Company facts
- Headquarters
- DE
- Industry
- Medical Practices
- Sector (NAICS)
- Information
- Peer
- Visionworks
- Website
- paicon.com
- Careers
- paicon.com/careers
Similar companies
Companies in the same industry as PAICON that are hiring now.
Questions about PAICON
- Is PAICON hiring?
- As of November 5, 2026, PAICON has no open roles in the job sources Metaintro tracks.
- Who are PAICON's customers?
- PAICON names 14 customers, including SRH, Genomics England, BioMed X, Co-founder, BioRN & HI-STEM, Leg&airy, Technology Entrepreneur, and PharmaSearch Ltd, Molecular Biologist & Geneticist (Oncology).