We live in a medication nation. 4.5 billion drug prescriptions will be prescribed by doctors like me this year, in the United States alone. That's 15 for every man, woman and child. And for most of us, our experience with this medication is often a confusing number of pills, instructions, side effects, one-size-fits-all dosing, which all too often we aren't taking as prescribed. And this comes at tremendous expense, costing us our time, our money and our health. And in our now exponential, connected, data-driven age,
我們住在藥物治療的國度。 今年,光是在美國, 像我這樣的醫生 就開出了 45 億張藥物處方。 男性、女性、小孩都算進來, 平均一人 15 張。 對我們大部分人來說, 我們對於藥物的經驗通常是 搞不懂要吃幾顆藥、用藥指示、 副作用、適用所有人的統一劑量, 我們經常會不依照處方來吃藥。 這樣造成的代價非常大, 成本是我們的時間、 我們的金錢,及我們的健康。 在這個指數成長、相互連結、 資料驅動的時代,
I think we can and we must do better. So let's take a dive at some of the challenges we have and some potential solutions. Let's start with the fact that many drugs don't work for those who are prescribed them. The top 10 grossing drugs in the United States this year, they only benefit one in four to one in 23 of who take them. That's great if you're number one, but what about everybody else? And what's worse, drugs, when they sometimes don't work, can still cause side effects.
我認為我們可以且必須要做得更好。 所以,我們來探討 一些我們面臨的困難 以及一些可能的解決方案。 咱們先來談一項事實: 許多藥物對於拿到 處方的人並不見得有用。 今年,美國總量排名前十名的藥物, 只對 1/4 到 1/23 的用藥者有效。 如果剛好對你有效,那很好, 但其他人怎麼辦? 更糟糕的是,藥物即使沒有效用, 有時仍然會引發副作用。 比如,阿斯匹靈——服用阿斯匹靈
Take aspirin -- about one in four of us who take aspirin to reduce our risk of cardiovascular disease are unknowingly aspirin-resistant and still have the same risks of gastrointestinal bleeds that kill thousands every year. It's adverse drug reactions like these that are, by some estimates, the number four leading cause of death in the United States. My own grandfather passed away after a single dose of antibiotic caused his kidneys to fail. Now, adverse drug reactions and side effects are often tied to challenges in dosing.
來減少心血管疾病的人當中有 1/4 並不知道自己有阿斯匹靈抗性。 他們仍然有同樣的風險 會發生消化道出血, 每年有數千人因消化道出血而死。 像這樣的藥物不良反應, 估計是美國排名第四的死因。 我自己的祖父過世了, 原因是一劑抗生素讓他的腎臟衰竭。 藥物不良反應和副作用 通常都和劑量選擇的困難有關。
I trained in pediatrics (little people) and internal medicine (big people). So one night I might have been on call in the NICU, carefully dosing to the fraction of a milligram a medication for a NICU baby. The next night -- on call in the emergency room, treating a 400-pound lineman or a frail nursing-home patient who, by most accounts, usually would get the same dose of medications from the formulary. Which would mean, most of the time I would be underdosing the lineman and overdosing the nursing-home patient. And beyond age and weight, we tend to ignore differences in sex and race in dosing.
我受的訓練是兒童的小兒科 和大人的內科, 所以我可能會在一晚 被找去新生兒重症監護室, 小心地給了一毫克的藥, 給新生兒重症監護室的寶寶。 隔天晚上——則被找去急診室, 治療四百磅重的架線工人 或是虛弱的護理之家病人, 大部分的說法都認為他們應該接受 同樣劑量的處方藥物。 那就表示,大部分的時候, 我給架線工的劑量是不足的, 給護理之家病人的劑量是過多的。 除了年齡和體重, 我們在決定劑量時 也傾向會忽略性別和種族。
Now, beyond this, we know we have a massive challenge with noncompliance or low adherence. Many of us who need to take our medications aren't taking them or are taking them incorrectly. You know, 40 percent of adults in the US over 65 are on five or more prescription medications. Sometimes 15 or more. And even small improvements in adherence can dramatically save dollars and lives.
除此之外,我知道 我們有個很大的困難, 就是不順從性和低依順性。 許多需要服藥的人不願服藥, 或以不正確的方式服藥。 在美國,有 40% 65 歲以上的人 通常服用 5 種以上的藥物。 有時甚至到 15 種以上。 只要依順性能有小小的改善, 就能省下很多錢、拯救很多性命。
So, as we think into the future, you think that where we are today, as we often hear about smart, personalized, targeted drugs, Internet of Things, gene therapy, AI, that we'd already arrived in this era of precision medicine. In reality, we still live in an age of empiric, trial-and-error, imprecision medicine. I think we can do better. What if we could reimagine ways to help make your medicine-taking easier? To get the right doses and combinations to match you? What if we could move beyond today's literal cutting edge of pill cutters and fax machines, to an era where we could have better outcomes, lower costs, saving lives and space in your medicine cabinet?
所以,在我們遙想未來時, 你認為我們現今的狀況, 我們通常會聽到智慧型、 個人化的標靶藥物, 物聯網、基因治療法、人工智慧, 好像我們已經到了 精準用藥的時代。 在現實中,我們仍然處在 靠經驗主義和試誤法的 不精準用藥時代。 我認為我們能做得更好。 如果我們能重新想像其他方式, 讓服藥變得更容易,會如何? 依你的狀況,選擇正確的劑量和組合? 如果我們能夠超越現今先進的 切藥器和傳真機, 進入一個新時代,有更好的結果、 更低的成本、拯救人命、 節省藥櫃中的空間,會如何?
Well, I think part of the solution is all the emerging ways that we can measure and connect our health care information. Today, we pretty much live in a reactive, sick-care world, siloed information that doesn't flow. We have the potential to move into a more continuous, real-time proactive world of true health care. And part of that starts with the emerging world of quantified self. We can measure so much of our physiology and behaviors today, and often it's siloed on our phones and scales, but it's starting to connect to our clinicians, our caregivers, so they can better optimize prevention, diagnostics and therapy. And when we can do that, we can do some interesting things.
我認為,解決方案有一部分在於 我們可以用來測量和連結 健康照護資訊的新興方式。 現今,我們算得上是住在 一個反應式、病人照護的世界, 資訊被儲存起來,不會流動。 我們有潛力可以做到更連續、即時、 主動式、真正健康照護的世界。 其中一部分開端是 量化自我的新興世界, 現今我們可以測量我們 許多生理狀況和行為, 這些資訊通常都儲存在 我們的手機和測量計當中, 但這些資訊已經開始連結到 我們的臨床醫生、照護者, 讓他們可以把預防、 診斷、治療做到最好。 當我們能做到這些時, 我們就能實行一些有趣的做法。
Take, for example, hypertension. It's the number one risk factor for early death and morbidity worldwide. Half of adult Americans, on approximation, have hypertension. Less than half have it well-controlled. It's often because it takes two or three different classes of medications. It's tough to do adherence and adjust your blood pressure medications. We have 500 preventable deaths from noncontrolled hypertension in the US every day. But now we're in the era of connected blood pressure cuffs -- the FDA just approved a blood pressure cuff that can go into your watch. There are now prototypes of cuffless radar-based blood pressure devices that can continuously stream your blood pressure. So, in the future, I could -- instead of spot-checking my blood pressure in the clinic, my doctor could see my real-time numbers and my trends, and adjust them as necessary, with the help of a blood pressure dosing algorithm or using the Internet of Things.
以高血壓為例。 在全世界,它是早死 和發病的第一名風險因子。 大約一半的成年美國人有高血壓, 不到一半的人有做好控制。 通常是因為他們需要服用 兩、三種不同類的藥物, 很難做到依順和調整 你的血壓藥物。 在美國,每天就有 500 件 因為高血壓未控制好 而致死的案例是可以避免的。 但我們現在所處的時代 已經發明出了脈壓帶—— 食品及藥物管理局(FDA)核准了 一種能和手錶結合的脈壓帶, 現在還有無帶式 雷達血壓裝置的原型, 可以持續提供你的血壓資訊。 所以,在未來,我可以 不用到診所去檢測我的血壓, 我的醫生仍然可以知道 我的即時數據和趨勢, 並依需要來做調整, 只要有血壓劑量 演算法的協助就能辦到, 或是使用物聯網也可以。
Now, technology today can do even more. My smartwatch, already today, has an EKG built in that can be read by artificial intelligence. I'm wearing a small, Band-Aid-sized patch, that is live-streaming my vital signs right now. Let's take a look. They're actually a little concerning at the moment.
現今的技術能做的還不只如此。 我現在的智慧手錶就 已有內建的心電圖, 可以用人工智慧來解讀。 我戴著一塊小型的 OK 繃尺寸貼片, 它現在就在即時傳輸 我的生命特徵資訊。 咱們來看看。 現在的這些數字 其實有點讓人憂心。
(Laughter)
(笑聲)
Now, it's not just my real-time vitals that can be seen by my medical team or myself, it could be my retrospective data, and again, that'd be used to modify dosing and medication going forward. Even my weight can be super-quantified; my weight, now my shape, how much body mass, fat, muscle mass I might have, and use that to optimize my prevention or therapy. And it's not just for the tech-savvy. Now, MIT engineers have modified wifi so we can seamlessly connect and collect our vital signs from our connected rings and smart mattresses. We can start to share this digital exhaust, our digitome, and even potentially crowdsource it, sharing our health information just like we share with our Google Maps and driving, to improve our -- not our driving, but our health experience globally.
我的醫療團隊或我自己能看到的 並不只有我的即時生命特徵資訊, 還能看到我的回溯資料, 可以參考這些資料來調整 後續的劑量和用藥選擇。 連我的體重也可以被超級量化。 我的體重、體型、 身體質量、脂肪、肌肉質量, 用這些資訊來將我的 預防或治療做到最好。 並不只有精通技術的人能用。 麻省理工學院的工程師 已經修改了無線上網, 讓我們可以做到無縫連結, 從連線的戒指和智慧床墊, 收集我們的生命特徵資訊, 我們能開始分享這些數位產出, 個人專屬的數位資料集, 甚至有可能將它做群眾外包, 分享我們的健康資訊, 就如同我們分享 Google 地圖和駕駛, 來改善我們的——不是我們的駕駛, 而是我們全球的健康體驗。
So, that's great. We can potentially now collect this information. What if your labs can go from the central lab to your home, to your phone, to even inside our bodies to measure drug levels or other varieties? And of course, we're in the age of genomics. I've been sequenced, it's just less than $1,000 today. And I can start to understand my pharmacogenomics -- how my genes impact whether I need high dose, low dose, or maybe a different medication altogether. Let's imagine if your physician or your pharmacist had this information integrated into their workflow, augmented with artificial intelligence, AI, or as I like to refer to it, IA -- intelligence augmentation, to leverage that information; to understand, of the 18,000 or more approved drugs, which would be the right dose and combination for you.
那很棒。 我們現在可能可以收集這些資訊。 若你的實驗室能從中央實驗室轉到 你的家中、你的手機上, 甚至你的體內, 來測量藥物濃度 或其他變數,會如何? 當然,現在是基因組學的時代。 我們已經能做定序, 現今的價格不到一千美元。 我能開始了解我的藥物基因體學, 我的基因會如何影響 我需要的劑量高低, 或是根本要換一種藥物。 咱們來想像一下, 如果你的醫生或藥師 能把這些資訊整合到 他們的工作流程中, 用人工智慧(AI)來增強, 我喜歡把它稱為 IA, 即:智慧式增強, 以發揮那些資訊, 來了解在一萬八千種以上的 被核准藥物中, 你需要的藥物組合和劑量是什麼。
So great, now maybe we can optimize your drugs and your doses, but the problem today is, we're still using this amazing technology to keep track of our drugs. And of course, these technologies evolve, there's connected dispensers, reminder apps, smart pill bottle caps that can text or tweet you or your mother if you haven't taken your medications. PillPack was just acquired by Amazon, so soon we may have same-day delivery of our drugs, delivered by drone. So, all these things are possible today, but we're still taking multiple pills. What if we can make it simpler?
很好,現在也許我們能幫你 把藥物和劑量最佳化, 但現今的問題是, 我們仍然在用這項了不起的技術 持續追蹤我們的藥物。 當然,這些技術會演進, 有連線的智慧藥盒、 提醒專用的應用程式、 智慧藥瓶蓋,如果你還沒有吃藥, 就會傳簡訊或推特訊息 給你或你母親。 PillPack 才剛被亞馬遜併購, 很快我們就會有藥品當日 遞送服務,由無人機送達。 所有這些在現今都是可能的, 但我們卻仍然在吃多種藥物。 如果我們能把它簡化呢?
I think one of the solutions is to make better use of the polypill. A polypill is the integration of multiple medications into a single pill. And we have these today in common over-the-counter cold and flu remedies. And there have been prevention polypill studies done, giving combinations of statins, blood pressure, aspirin, which in randomized studies have been shown to dramatically reduce risk, compared to placebo. But these polypills weren't personalized, they weren't optimized to the individual. What if we could optimize your personalized polypill? So it would be built for you, based on you, it could adapt to you, even every single day. Well, we're now in the era of 3D printing. You can print personalized braces, hearing aids, orthopedic devices, even I've been scanned and had my jeans tailored to fit to me.
我認為其中一個解決方案 就是善用複方製劑。 複方製劑是把多種藥物 整合到單一藥錠中。 現今我們在一般的無處方 傷風感冒藥物中就有用複方製劑。 已經有人做過了 預防藥複方製劑的研究, 結合了施德丁、血壓、阿斯匹靈, 在隨機研究中已經發現這些組合 相對於安慰劑,能大大減少風險。 但這些複方製劑並沒有被個人化, 沒有針對個人做最佳化。 若我們為你製作最好的 個人化複方製劑,如何? 它會是為你打造的, 以你為基礎,它適合你, 且可以每天取得。 在這 3D 列印的時代,你能列印出 個人化的支架、 助聽器、骨科用裝置, 我甚至接受掃瞄之後 取得了客製化的牛仔褲。
So this got me thinking, what if we could 3D-print your personalized polypill? So instead of taking six medications, for example, I could integrate them into one. So it would be easier to take, improve adherence and potentially, it could even integrate in supplements, like vitamin D or CoQ10. So with some help -- I call these "IntelliMeds" -- and with the help of my IntelliMedicine engineering team, we built the first IntelliMedicine prototype printer.
這讓我去思考, 如果我們能把個人化的複方製劑 列印出來,會如何? 比如,就不用一次吃六種藥物, 我可以把它們整合成一種。 這樣吃藥就更容易了, 依順性也能改善, 還有可能把補給品也整合進來, 比如維生素 D 或輔酶 Q10。 靠著一些協助——我稱它們為 「智慧藥物(IntelliMeds)」—— 靠著我的智慧藥物工程團隊協助, 我們打造了第一台 智慧藥物原型列印機。
And here's how it works: instead of full tablets, we have small micromeds, one or two milligrams each, which are sorted and selected based on the dose and combination needed for an individual. And of course, these would be doses and combinations you could already take together, FDA-approved drugs. We could change the pharmacokinetics by professionally layering on different elements to the individual micromeds. And when we hit print, you print your combination of medications that might be needed by you on any individual day. And we'd start with, again, generic drugs for the most common problems. About 90 percent of prescribed drugs today are low-cost generics. And once we've printed the pill, we can do some fun bells and whistles. We could print the name of the patient, the date, the day of the week, a QR code. We could print different meds for tapering for a patient on a steroid taper, or tapering from pain medications.
它的運作方式是:用微型藥物, 而非完整的藥錠, 每個只有一或二毫克, 會根據個人所需要的 劑量和藥物組合來挑選。 當然,這些是你本來就能 一起服用的劑量和組合, FDA 核准的藥物。 我們能改變藥物代謝動力學, 做法是針對個別的微型藥物, 將不同元素以專業方式層疊上去。 當我們按下列印鍵, 你就能印出你在任何一天 可能需要的藥物組合。 同樣的,我們也是從治療 最常見問題的非專利藥物做起。 現今有 90% 的處方藥 都是低成本的非專利藥物。 一旦我們把藥錠列印出來, 我們就能再做些有趣的額外功能。 我們能列印出病人的名字、 日期、星期幾、一個 QR 碼。 我們能為在做類固醇減藥 或止痛藥減藥的病人 列印出不同的藥物供減藥用。
So, this is actually a look at our prototype IntelliMedicine printer. See, I'll unveil it here. It has about 16 different silos, each containing individual micromeds. And I can now adjust on the software individual dosings. And when I do that, the robotic arm will adjust the height of these spansules and the micromeds will release. I can now -- The automated process would rotate and cycle through, to make sure the micromeds are loaded. And when I hit print, these will all fall through the device, I now pull out my personalized printed polypill with the doses and medications meant for me. And we can take a look, if you look back to the slides, you can see the whole process, we can see the drug silos being selected, the pills doing down the different silos, and being collected in the individual capsule.
讓各位看看我們的 原型智慧藥物列印機。 在此揭幕。 它有 16 個不同的筒倉, 每個當中都裝有個別的微型藥物。 我可以透過軟體 來調整個別的劑量。 當我操作軟體時, 機械手臂就會調整 這些長效膠囊的長度, 微型藥物就會被釋出。 我現在可以—— 它會自動旋轉和輪轉, 確保微型藥物有被裝載上去。 當我按下列印鍵, 這些都會透過裝置落下, 現在我可以取出我的 個人化列印複方製劑, 它的劑量和內含藥物 都是針對我做的。 我們可以回頭看一下投影片, 你們可以看到整個過程, 我們能看到藥物筒倉被選取, 藥錠從不同的筒倉落下, 被收集放入個別的膠囊。
Now, this is great, I can potentially print my meds based on me, instead of taking six pills. I can now be looking at my individual dosing. My smartwatch is looking at my blood pressure: I needed an adjustment in my blood pressure medicines, my coumadin level. My blood is too thin, so I lower my micromed dose of coumadin, a blood thinner. So, this could be smartly adapted, day to day, programmed by my physician or cardiologist. And you can imagine that larger printers, fast printers like this, could be in your corner pharmacy, in your doctor's office, in a rural clinic. But it could eventually merge and shrink to small ones that could be in your home with integrated cartridges like this that are delivered by drone. Could print your personalized polypill, each morning on your kitchen or your bathroom cabinet. And this could evolve, I think, into an incredible way to improve adherence in medications across the globe.
這很棒, 我可以依我個人需求 來列印我的藥物, 不用吃六種藥物。 我現在可以察看我的個別劑量, 我的智慧手錶在看我的血壓, 我需要調整我的血壓藥物, 我的華法林濃度,我的血液太稀, 所以我降低了我的華法林 微型藥物劑量,它會稀釋血液。 可以智慧地做調整, 配合每天的狀況, 由我的內科醫生 或心臟科醫生來製訂計畫。 你們可以想像像這樣的 列印機,但更大、更快, 擺放在你家附近街角的藥房裡、 你的醫生的辦公室裡、 鄉村的診所裡。 最終,它可以被合併和縮小, 成為小型個人家用列印機, 有像這樣的整合藥筒, 由無人機來遞送。 放在你的廚房或是浴室儲存櫃中, 每天列印出你的個人化複方製劑。 我認為,這有可能會演進, 成為一種很棒的方式, 來改善全球的依順性。
So, I hope we can reimagine the future of medicine in new ways, moving from polypharmacy, one-size-fits-all, low adherence, complications to an era of personalized, precise, on-demand medications that can take us and individualize our own health and health and medicine around the planet.
我希望我們能夠以新的方式 來重新想像藥物的未來, 從多重用藥、所有人通用的劑量、 低順從性、複雜混亂, 轉變為個人化、精確、 依需要來供應的藥物, 將我們自己的健康給個人化, 也將世界各地的健康 和藥物給個人化。
Thank you very much.
非常謝謝。
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Host: Daniel, that's kind of awesome. Really cool. Question for you, though. How long is it until, say, that nursing-home patient that you mentioned is able to print their pills in their home?
主持人:丹尼爾,那真的很棒。 非常酷。 但,有問題想請教。 還要多久才能讓, 比如,你提到的護理之家病人, 能夠在他們自己的家中 列印他們的藥錠?
Daniel Kraft: Well, again, this is just a prototype. We think that the regulatory route [may] be automated compounding, and especially in nursing homes, folks are taking multiple medications, and they're often mixed up, so it would be a perfect place to start with these technologies. These aren't going to evolve and start with printers on your bathroom counter. We need to be intelligent and smart about how we roll these things out, but realizing there's so many challenges with dosing, adherence and precision, and now that we have all these amazing new technologies that can integrate and be leveraged, I think we need approaches like this to really catalyze and foster a true future of health and medicine.
丹尼爾克拉夫特: 再次強調,它只是樣本機。 我們認為還有待改善的部分 是使其能夠自動合成, 特別是在護理之家, 那裡的人會服用多種藥物, 他們常常會搞混, 護理之家是這些技術 最完美的起始點。 這些技術不可能從你浴室 櫃台上的列印機開始和演進。 我們必須要以很聰明的方式 來推出這些東西, 但要知道,在劑量、依順性, 和精準度上都還有許多困難挑戰, 現在我們有這麼多了不起的 新技術,可以被用來整合, 我認為我們需要這樣的新方法, 來真正催化 和促進健康和藥物的真正未來。
Host: Great, thank you. DK: Thanks.
主持人:好極了,謝謝你。 丹尼爾:謝謝。
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