{"id":19544,"date":"2026-09-24T05:07:58","date_gmt":"2026-09-24T08:07:58","guid":{"rendered":"https:\/\/rtmedical.com.br\/tmp-en-1790237277976\/"},"modified":"2026-09-24T05:08:07","modified_gmt":"2026-09-24T08:08:07","slug":"bcrf-ventures-fund-clairity","status":"publish","type":"post","link":"https:\/\/rtmedical.com.br\/en\/bcrf-ventures-fund-clairity\/","title":{"rendered":"BCRF Launches $100M Fund, Invests in Clairity"},"content":{"rendered":"

The Breast Cancer Research Foundation (BCRF)<\/strong>, the largest private funder of breast cancer research in the United States, has launched BCRF Ventures<\/strong>, a venture philanthropy fund targeting $100 million over five years<\/strong> \u2014 and its first check went to a radiology company. The recipient is Clairity<\/strong>, the startup founded by breast radiologist Connie Lehman, MD, PhD, whose AI estimates a woman’s five-year risk of developing breast cancer from a routine screening mammogram. The fund was announced on September 22 at the Clinton Global Initiative Annual Meeting in New York.<\/p>\n

\"Chart
The fund launches with $23 million; the remaining $77 million still has to be raised.<\/figcaption><\/figure>\n

How BCRF Ventures is structured<\/h2>\n

The fund starts with $23 million<\/strong> in seed donations. The largest, an $11 million<\/strong> lead gift, came from philanthropists Karen and Rob Hale; Karen Hale co-chairs BCRF’s board of directors. According to Fortune, the other $12 million came from a bequest by an unnamed donor. That leaves roughly $77 million to raise to hit the target.<\/p>\n

The thesis is explicitly venture philanthropy. Instead of making a grant to a laboratory, the foundation takes equity in early-stage companies building products for breast cancer prevention, detection, diagnosis and treatment. Any financial returns flow back into the fund and are redeployed into new companies \u2014 what BCRF calls an “evergreen” source of capital. The planned portfolio is 20 to 30 companies<\/strong> over five to seven years, spanning diagnostics, targeted therapies, immuno-oncology and emerging technologies. New proposals will be considered starting in 2027.<\/p>\n

The stated target is the so-called valley of death: the gap between academic proof of concept and clinical development, when an idea has left the bench but is still too risky for conventional venture capital. BCRF president and CEO Donna McKay framed the problem as some of the most promising ideas being lost at the very moment they are ready to move beyond the lab.<\/p>\n

Why Clairity was the first bet<\/h2>\n

The size of the Clairity investment was not disclosed. The choice nonetheless works almost as a showcase for the model, because the company has already travelled the road the fund wants to shorten. Lehman, a Harvard professor of radiology, breast imaging specialist and long-time BCRF-funded investigator, founded Clairity in 2020 to commercialise the image-based risk models her group had been developing for years. She also serves as CEO.<\/p>\n

Its flagship product, Clairity Breast<\/strong>, received FDA De Novo authorization<\/strong> in 2025 \u2014 the first granted to an AI platform for breast cancer risk prediction. As we reported when the first clinical patient received a Clairity score in Boston<\/a>, the model was trained on roughly 421,000 mammograms and externally validated on more than 120,000 exams. The second milestone came in 2026, when the NCCN guidelines for breast cancer screening and diagnosis were updated to include AI analysis of the mammogram as a risk assessment option, with a five-year risk threshold of \u22651.7%<\/strong> to define increased risk, periodic reassessment and risk identification starting at age 35.<\/p>\n

In a statement, Lehman said BCRF Ventures shows what becomes possible when promising science has the resources to move rapidly from discovery to real-world impact, adding that the company can now accelerate its innovations. The foundation highlighted the tool’s potential to broaden equitable access to earlier care.<\/p>\n

What image-based risk changes<\/h2>\n

To see why a research foundation would back this kind of product, it helps to recall how risk is estimated today. The classic models \u2014 Gail and Tyrer-Cuzick (IBIS) \u2014 rely on questionnaires: age, family history, age at menarche and first birth, prior biopsies and sometimes breast density. They perform reasonably in populations resembling those they were built on, tend to underestimate risk in other groups, and require someone to collect and enter data that are often missing from the chart.<\/p>\n

Image-based models flip the logic: the information is already in the exam the woman just had. Parenchymal texture patterns, the distribution of fibroglandular tissue and subtle asymmetries feed the prediction with no form to fill in. Evidence that the mammogram carries this signal keeps accumulating. A Swedish study in Radiology showed that AI algorithms flag breast cancer risk up to a decade before diagnosis<\/a>, and other work tracked how AI-estimated risk evolves from one exam to the next<\/a>.<\/p>\n

Acceptance matters too. A survey of 319 patients found that eight in ten women are comfortable with AI-based risk assessment<\/a> \u2014 more than those preferring a history-based estimate. The bottleneck, then, is less the patient than the practice: who communicates the score, what happens to a woman flagged as increased risk, and who pays for the supplemental MRI.<\/p>\n

Implications for radiologists and imaging practices<\/h2>\n

BCRF’s move confirms that risk prediction has become its own category within mammography AI, distinct from detection. Detection tools compete on reading efficiency; risk tools compete on screening design<\/em> \u2014 interval, supplemental modality, referral to genetic counselling or to risk-reduction strategies. With guideline inclusion, the category now has a clinical anchor it previously lacked.<\/p>\n

For practices, that raises operational questions well before any purchasing decision: whether the report template has a place for a quantitative five-year risk, how results are communicated to patients and referrers, and whether there is capacity to absorb the additional MRI and ultrasound that a risk-stratified programme generates. In Brazil and much of Latin America, where Clairity Breast has no Anvisa registration and public screening still struggles with basic coverage, the appeal is the reverse: using an exam already performed to steer scarce supplemental imaging toward the women who need it \u2014 provided the model is validated in local populations.<\/p>\n

Limitations and what to watch<\/h2>\n

A few caveats. First, this is an institutional announcement: there are no new Clairity performance data, and the investment amount was not disclosed. Second, 77% of the fund’s target still has to be raised, and new investments will not begin until 2027. Third, venture philanthropy carries a built-in tension worth watching: the foundation now has a financial stake in the success of products whose inventors it also funds as researchers \u2014 which makes independent validation of these tools all the more important.<\/p>\n

Even so, the signal is clear. One of the world’s largest funders of cancer research has decided that some of its money works harder as company equity than as a lab grant \u2014 and it chose a radiology AI to open the portfolio.<\/p>\n

Source:<\/strong> Health Imaging \/ Radiology Business<\/a>; BCRF<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

The Breast Cancer Research Foundation launches a $100M venture philanthropy fund; its first investment goes to Clairity’s mammography risk AI.<\/p>\n","protected":false},"author":1,"featured_media":19494,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"ngg_post_thumbnail":0,"_rt_cluster":"","fifu_image_url":"","fifu_image_alt":"","footnotes":""},"categories":[102,100],"tags":[],"class_list":["post-19544","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","category-radiology"],"aioseo_notices":[],"rt_seo":{"title":"","description":"The Breast Cancer Research Foundation launches a $100M venture philanthropy fund; its first investment goes to Clairity's mammography risk AI.","canonical":"","og_image":"","robots":"index,follow","schema_type":"Article","include_in_llms":true,"llms_label":"BCRF Ventures invests in Clairity","llms_summary":"On Sept 22, 2026 the Breast Cancer Research Foundation launched BCRF Ventures, a venture philanthropy fund targeting $100M over five years ($23M seed, including an $11M gift from Karen and Rob Hale). Its first investment is Clairity, Connie Lehman's company whose AI predicts five-year breast cancer risk from a mammogram, FDA De Novo authorized in 2025 and included in NCCN guidelines in 2026.","faq_items":[],"video":[],"gtin":"","mpn":"","brand":"","aggregate_rating":[]},"_links":{"self":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/19544\/"}],"collection":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/"}],"about":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/types\/post\/"}],"author":[{"embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/users\/1\/"}],"replies":[{"embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/comments\/?post=19544"}],"version-history":[{"count":1,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/19544\/revisions\/"}],"predecessor-version":[{"id":19551,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/19544\/revisions\/19551\/"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/media\/19494\/"}],"wp:attachment":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/media\/?parent=19544"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/categories\/?post=19544"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/tags\/?post=19544"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}