Priscilla Chan on Broadening Rare-Disease Research

A short argument for putting research tools in more hands, with context on spinal muscular atrophy.

PCPriscilla Chan登壇者
チャンネル
No Priors: AI, Machine Learning, Tech, & Startups
公開日
2026年7月7日
動画
1:03
読了時間
1 分
原文
英語
YouTube で開く
スクロールすると動画は右下に小さくなって再生を続けます。字幕は閲覧言語に合わせて切り替わります。
閲覧言語2 言語で読めます
この記事はまだ日本語に翻訳されていないため、英語の原文を表示しています。
要約

30 秒でわかる

Priscilla Chan argues that rare diseases may be overlooked by research strategies focused on large populations. She suggests broader access to tools could support more targeted research; SMA already has active research and approved treatments.

  1. 1A long tailCommon disease categories contain many distinct subtypes, alongside rare diseases.
  2. 2Broader accessChan argues for giving more researchers tools to pursue neglected questions.
  3. 3SMA contextSMA has active research and approved treatments.

ポイント

  1. Disease categories include many subtypes.
  2. Rare diseases can receive less attention in population-focused research.
  3. Chan favors broader access to research tools.
  4. SMA already has approved treatments.
全文

チャプターごとに整えた全文を読む

文字起こしのみ
01

Researching the long tail

Priscilla Chan argues that disease categories contain many subtypes, and that rare conditions may receive less attention when research focuses on interventions affecting the largest numbers of people.

Priscilla Chan argues that disease categories contain many subtypes, and that rare conditions may receive less attention when research focuses on interventions affecting the largest numbers of people.

She proposes putting research tools in more people’s hands so that individuals and smaller groups can pursue conditions they care about. As an example, she mentions spinal muscular atrophy (SMA).

Chan suggests that studying a rare disease can also reveal broader biological mechanisms. This is an argument for widening research participation, not a guarantee that a particular tool or project will produce a treatment.

SMA is already the subject of active research and has approved treatments; it should not be understood from the clip’s headline as a disease nobody studies. For example, the FDA has approved gene therapy for specified SMA patients. [FDA announcement](https://www.fda.gov/news-events/press-announcements/fda-approves-gene-therapy-treatment-spinal-muscular-atrophy).

同じチャンネルの記事

38:06EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月29日ポッドキャスト · 3 人Serval’s Jake Stauch on coding agents for enterprise ITゲスト Jake Stauch · ホスト Sarah Guo, Elad GilStauch explains why Serval is challenging ServiceNow, how it approaches permissions and approvals, and why background agents remain difficult to deploy safely.エンタープライズ AIコーディングエージェントWorkflow automation+2
39:23EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月15日ポッドキャスト · 2 人The Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of Cybersecurityホスト Sarah Guo, Elad GilOpenAI's president explains why solving open math problems is a proof point for science, how proactive agents change product form, and why security spending must exceed software spending.セキュリティと安全性AI security安全性とガバナンス+3
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月9日ポッドキャスト · 2 人10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledgerホスト Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.オープンソースとコミュニティOpen-weight modelsReinforcement Learning+3
35:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月2日ポッドキャスト · 2 人Compute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That Ratioホスト Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.インフラとデプロイInferenceAI cost & performance+3
42:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年9月24日ポッドキャスト · 2 人They Paid $7.7 Billion for a Broker — and Intend to Do One Deal a Yearホスト Sarah Guo, Elad GilSequence Holdings co-founder Michael Lee tells No Priors why owning a market leader, not selling it software, is how AI actually remakes an incumbent.企業と戦略エンタープライズ AIAI Strategy+3
38:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年9月18日ポッドキャスト · 2 人Diffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Siliconホスト Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.モデルと学習InferenceAI cost & performance+3