01 / THE SIGNAL

我们发现了什么

我们使用机器学习和计算机视觉来优化生产。我们建立了高效的制造运营体系,并将业务营收增长到 5,000 万美元。

  • 来源:Hacker News(首次 2026-09-03 · 最近 2026-09-04)
  • 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
  • 商业模式:待核验
  • 主题:独立产品
  • 初筛评分:31.1/100 · 收录 2 次
#独立开发#待验证#产品发现
02 / SOURCE & EVIDENCE

证据,比故事更重要。

发现产品或需求信号,暂未获得可核验的商业证据。

规则清洗与初筛,未经人工商业核验。原文语境、实际客户和付费情况仍需自行验证。

引用与数字披露

来源类型(原作者自述/第三方测算/媒体转引)需采集端标注,本版尚未落字段。

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中文辅助译文(来源摘要)

嗨 HN,我是 Lloyd,RonanRx(https://ronanrx.com/ )的两位联合创始人之一。我们正在打造一家纵向整合的制药公司,提供涵盖处方开具、远程医疗、复方配制、生产制造和配送的软件。我们从 GLP-1 类药物和多肽开始。通往 RonanRx 的道路相当非传统。在疫情期间,我建造了美国最大的口罩制造工厂之一。我们一天能生产一百万只口罩。我们将聚丙烯原料颗粒转化为成品托盘口罩。我拥有来自我的 YC W10 公司的软件背景,因此我们采用了软件方式来建造工厂。我们使用机器学习和计算机视觉来优化生产。我们还几乎对所有环节进行了纵向整合。这很成功。我们建立了高效的制造业务,并将营收增长至 5000 万美元。后来人们真的不再关心口罩了。也情有可原。大约同一时期,我决定尝试减掉在建造工厂期间增加的体重。我有六个月只吃鸡肉。虽然这种饮食带来了一些效果,但我遇到了平台期。我的医生建议我使用 tirzepatide,这是一种 GLP-1 类药物。对我而言,减重只是开始。对食物的执念消失了。我对其他强迫性行为的兴趣也降低了。我不再刷 Instagram,也戒掉了咬指甲。但这只是开始。我天生患有先天性心脏缺陷,称为主动脉瓣狭窄。我一生中医生都告诉我,我在 40 多岁时需要进行开心手术(我现在 45 岁)。在使用 tirzepatide 仅 18 个月后,我的心脏科医生开始认为(至今仍认为)我的手术可以推迟到我 70 或 80 岁时再进行。这一切都发生在我决定下一步做什么的时候。我想继续从事制造业。我不想再打造一款可能被前沿模型复制的产品。

制药制造是我能找到的数字、物理、生物和监管基础设施的最佳组合。让我困扰的是所有这些环节——远程医疗、电子健康记录、处方、配药软件、生产、运输——有多么脱节。没有一家公司能囊括所有环节。GLP-1 类药物有少量预定义剂量,但患者显然并非标准化:他们的反应不同,减重速度不同,经历的副作用不同,可能需要非常不同的剂量。复方药房可以配制定制处方,但它们的运作方式不像软件公司。工作流是手动的、碎片化的,并且与患者数据脱节。我们的目标是用 RonanRx 将这些环节连接起来。患者可以直接联系我们,或由医生转介。一旦患者进入我们的系统,我们会收集病历、当前用药、实验室检查以及可穿戴设备的数据。我们的软件会跟踪处方从药物配方、复方配制、质量检测到配药和配送的全过程。最有趣的功能是反馈循环。在患者接受治疗的过程中,他们的反应成为数据,可供其医生用来调整治疗方案。我们让医生始终留在反馈循环中。我们通过销售我们生产的药物来盈利。由于人们可以直接向我们购买,他们的价格通常便宜 3 到 10 倍。我们能做到这一点,是因为我们从分子环节起步,并拥有从制造到处方、配药和配送的整个技术栈,而不是在每个环节支付一连串中间商的费用。我们从 GLP-1 类药物和多肽开始,因为这是我个人遇到问题的地方;然而,我们对针对特定患者的制药制造潜力更感兴趣。我们非常希望听到你的反馈,尤其是如果你曾构建过药房、制造、临床基础设施、电子健康记录或任何其他受监管的软件。这个模型中有许多假设需要验证。

译文由上游机器翻译生成,可能有误;判断请以英文原文为准。

英文原文(来源本站未改写)

Hi HN, I’m Lloyd, one of two founders of RonanRx ( https://ronanrx.com/ ).We are building a vertically integrated pharmaceutical company with software for prescribing, telehealth, compounding, manufacturing, and delivery.We are starting with GLP-1s and peptides.The path to RonanRx is fairly unconventional.During the pandemic, I built one of the largest mask manufacturing factories in the US.We could make a million masks in a day.We converted raw polypropylene pellets into finished pallets of masks.I had a background in software from my YC W10 company, so we took a software approach to building our factory.We used machine learning and computer vision to optimize production.

We also vertically integrated almost everything.It worked.We built an efficient manufacturing operation and grew the business to 50 million dollars in revenue.Then people actually stopped caring about masks.Fair enough.Around the same time, I decided to try and lose the weight I had gained while building the factory.I ate nothing but chicken for six months.While this diet got some results, I plateaued.My doctor suggested tirzepatide, a GLP-1 medication.For me, losing weight was only the beginning. "Food noise" was gone.I showed less interest in other compulsive behavior.I stopped scrolling Instagram and quit biting my nails.But that was just the beginning.

I was born with a congenital heart defect called aortic stenosis.My whole life doctors told me I'd need open heart surgery in my 40s (I am 45 now).After just 18 months using tirzepatide, my cardiologist’s began to think (and still thinks) my surgery could be pushed back until I am 70 or 80.This was all happening when I was deciding what to work on next.I wanted to keep working on manufacturing.I didn't want to build another product that could be replicated by a frontier model.Pharmaceutical manufacturing was the best combination of digital, physical, biological, and regulatory infrastructure I could find.

The thing that bothered me was how disconnected all of the pieces were: telehealth, EHR, prescriptions, dispensing software, production, shipping.No one company has it all.GLP-1s come in a handful of predefined doses, but patients obviously aren't standardized: they respond differently, lose weight at different rates, experience different side effects, and may need very different doses.Compounding pharmacies can fill customized prescriptions, but they are not built like software companies.Workflows are manual, fragmented, and disconnected from the patient’s data.It's our goal to connect those pieces with RonanRx.Patients either come to us directly or are referred by a physician.

Once a patient is in our system, we collect medical records, current meds, labs, and data from wearables.Our software follows the prescription through drug formulation, compounding, quality testing, and drug dispensing and distribution.The most interesting feature is the feedback loop.As the patient is undergoing treatment, their response becomes data that can be used by their doctor to modify the treatment.We keep the doctor in the feedback loop.We make money by selling drugs we manufacture.Because people can buy directly from us, their price is usually 3x-10x more affordable.

We can do this because we start at the molecule and own the entire stack from manufacturing through prescribing, dispensing, and delivery, instead of paying a chain of middlemen at every step.We are beginning with GLP-1s and peptides since this was where I personally experienced the issue;however, we are more interested in the potential of patient-specific pharmaceutical manufacturing.We would love your feedback, especially if you have built pharmacy, manufacturing, clinical infrastructure, EHRs, or any other regulated software.There are a lot of assumptions in this model that should be tested.

出处https://ronanrx.com抓取日期 · 采集源 Hacker News

03 / EVIDENCE GAPS

这条还缺什么证据?

下面每条都由本条已有字段推出(等级、理由、商业模式、来源次数、是否演示), 本站不生成推测性结论;通用验证方法放在方法论页。

  • 可核验的收入或付费证据查官网定价页与付费口径;第三方数据源(如 GetLatka)只作旁证,需标注来源与时点。
  • 商业模式未定确认按席位/按用量/授权还是开源托管版收费;开源项目另查 LICENSE 与是否存在付费版。

通用验证清单(谁有这个问题/谁愿意付费/一个人能交付哪一小步)见我们的筛选方法。

04 / SIGNAL HISTORY

发现时间线