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Another look at the Law of Diminishing Returns
重新审视边际效益递减规律
In Part 1 of this blog, I showed that the linear decline in IRR can be fully explained by the Law of Diminishing Returns as a natural and unavoidable consequence of prioritizing a limited set of investment opportunities. In particular, I demonstrated that prioritizing a limited set of random investment opportunities by their IRR over time produces a perfect linear decline in IRR, which passes right through 0%, exactly as we have seen with Pharma’s R&D productivity. Moreover, the IRR plot of prioritized investment opportunities follows a perfect linear decline regardless of their initial distribution.
在这篇博客的第一部分，我指出，内部收益率的线性下滑能由边际效益递减规律所充分解释，而这又是对有限的投资机会排优先级而造成的自然而然、却又不可避免的结果。特别是，我说明了对一个由随机的、以内部收益率为特征的投资机会的有限集合排优先级，将会造成内部收益率的完美线性下降，而且还会击穿0%，正如我们在制药企业的研发效率上已经看到的那样。不仅如此，无论初始分布如何，对内部收益率排优先级而生成的曲线都呈现完美的线性下降趋势。
In fact, the only condition required to guarantee that a sequence of investments follows the Law of Diminishing Returns in this way, is that the total number and/or potential value of investment opportunities is ultimately limited. In essence, there must be some critical limiting factor, which is both exhaustible and in short supply.
实际上，令边际效益递减规律在投资方面奏效的唯一限制性因素是投资机会的总数量和/或潜在价值最终是有限的。 从本质上讲，必须有一些关键的限制因素，它们既可被用尽，又供不应求。
So what could be the ultimate limiting factor in Pharma R&D? It is certainly not the number of potential new drugs itself, since the number of possible drug-like molecules has been estimated to exceed the number of atoms in the entire solar system.
所以，什么是制药企业研发的最根本限制因素？这当然不是潜在的新药分子的数量问题，因为类似药物的分子的数量估计超过了整个太阳系中的原子数量。
And it is not the unmet clinical need or potential value of new drugs, since we spend more each year on healthcare for our growing and ageing population. Indeed, there appears to be no end to human suffering, and we will always get sick and die at least once in our lives, despite medical progress.
这也不是未满足的临床需求或新药的潜在价值的问题，因为老龄化日趋严重，我们每年花在医疗上的钱都在增长。确实，人类的痛苦永远不会消失，无论医疗如何发展，我们都将生病和死亡至少一次。
The real answer, as I explain below, is that we are rapidly running out of viable new drug targets that could possibly be addressed with existing approaches and technologies.
真正的答案，如我下面所述，是我们正在快速地消耗已经所剩无几的可行新药靶点，这些靶点是通过现有方法和技术所能利用的。
A diminishing pool of viable new drug targets
可用的新药靶点日渐减少
Ultimately, all drugs work by interacting with at least one specific molecule or “drug target” in the body. Furthermore, all such drug targets must satisfy all of the following criteria in order to provide a viable source of effective new drugs:
最终，所有药物都与体内至少一种特定的分子、或称为“靶点”的相互作用而起效。此外，所有靶点必须同时满足所有下面这些条款，才能提供研发有效新药时可以使用的原型：
1. Clear correlation or relationship with human disease
2. Can be targeted with small molecules or large proteins
3. Not already exploited by existing approved drugs
4. Not already tested and failed due to mechanism of action
5. Commercially viable, linked to a clear unmet need
1. 与人类疾病的清晰关系或联系
2. 能被小分子或大的蛋白质所靶向
3. 尚未被已获批准的药物所使用
4. 作用机制未被此前的测试证明为失败
5. 商业上可行，与清晰的未满足的需求相对应
According to the Human Protein Atlas, there are 19,613 proteins encoded by the human genome. Of these, 14,545 (74%) have no known link or relationship with disease, which rules them out as potential new drug targets because they fail to meet criterion 1 above. Perhaps these proteins are non-essential, as any deficiencies can be compensated by other proteins or pathways; or perhaps they are essential, however any deficiencies are lethal before birth so they never have the chance to cause any disease. In any case, we have no reason to believe that targeting these proteins will do anything for any known human disease.
根据《人类蛋白质图谱》，人类基因组编码了19,613种蛋白质。其中，14,545种（74%）与疾病没有已知的关联或联系，这让它们无法作为潜在的新药靶点，从而出局了，因为它们无法满足上述条款1。可能这些蛋白质并不是必须的，因为任何的缺少都能被其他蛋白质或途径来弥补；也可能它们是必须的，但缺乏它们中的任何一种都会导致无法产生新生命，所以它们从来没有机会引起任何疾病。无论如何，我们没有任何理由认为，以这些蛋白质为靶点会对任何已知的人类疾病有疗效。
Now of the 5,068 proteins that have any link to disease, 3,131 (16% of all human proteins) are considered to be “undruggable”, either because they have no obvious pocket capable of binding small molecule drugs, or because they are intracellular and thus inaccessible to large proteins that cannot penetrate the cell membrane. We must rule out these proteins as potential new drug targets because we currently have no way to target them, so they fail to meet criterion 2 above.
这样，其中5,068种蛋白质与疾病有关联，3,131种（人类蛋白质总数中的16%）被认为是“不可成药”，要么它们明显的不可能与小分子药物相结合，要么它们在细胞内部，而大的蛋白质无法穿透细胞膜。我们必须排除这些潜在可能作为新药靶点的蛋白质，因为我们当前找不到靶向它们的办法，所以它们无法满足上述的条款2。
This leaves only 1,937 potential drug targets (10% of all human proteins), but 672 of these have already been fully exploited as proven drug targets by current approved drugs. Once a new drug target is first identified and exploited by an original first-in-class drug, any “me-too” drugs that follow tend to provide little, if any incremental benefit or value to patients, and profit mostly by taking market share from the original drug. In essence, drug targets are an exhaustible resource rather like oil: once we have tapped its potential value, it’s gone; we can’t have our cake and eat it. Therefore, we must also rule out these proteins as potential new drug targets, simply because they are no longer new, and they fail to meet criterion 3 above.
这样排除后，只剩下1,937种潜在的药物靶点（人类蛋白质总数中的10%），但其中672种已经被证明为靶点，并被当前已获批准的药物所充分利用。一旦一个新药靶点被确认，并被一个原创的first-in-class药物所利用，任何跟随的me-too药物往往只能为患者带来微乎其微的益处或价值，但它们却能抢夺最初上市的药物的市场份额，而这是它们的主要利润来源。本质上，药物靶点是可被用尽的资源，就像原油：一旦我们把其潜在价值开采出来，它就消失了；我们不可能去吃已经在肚子里的蛋糕。因此，我们必须指出，这些蛋白质之所以被标记为潜在的靶点，仅仅是因为它们已经不再是新的了，它们无法满足上述的条款3。
So now we are left with only 1,265 potential new drug targets:
算到现在，我们只剩下1,265个潜在的新药靶点：
At first glance, it seems that we have more than twice as many potential new drug targets left to find and exploit as those we have already exploited, so we should not be overly concerned about running out any time soon. But what about the other two criteria, 4 and 5? How many of these potential drug targets have already been tested but failed to yield any drugs due to mechanism of action? How many have not yet been tested, but are still unlikely to yield any drugs? And how many will yield only drugs that are not commercially viable in any case?
初看上去，我们似乎有两倍于已被采用的靶点尚未被探索和采用过，所以我们不应该特别担心靶点被耗尽的时刻会很快到来。但，如果考虑另外两个条款、条款4和条款5呢？有多少潜在靶点的作用机制被测试为失败？有多少靶点尚未被测试，但仍然不太可能形成药物？有多少靶点可以形成药物，但在商业上无论如何都不可行？
Now this is where the numbers get a bit fuzzy because they are not widely reported (or at least I could not easily find them), but we can make some very rough estimates.
现在这个数字比较模糊，因为相关报告并不多（至少我不能轻松地找到），但是我们可以做一些粗略的估算。
First, let’s say that about 50% of all drug targets we have ever fully tested produced at least one approved drug, while the other 50% failed to deliver any drug at all, due to fundamental reasons (e.g., safety) based on mechanism of action. Given that we now have approved drugs for 672 drug targets, this would imply that we have already fully tested a similar number of drug targets without ever producing any drug, so we can rule these out as potential new drug targets because they are not new, and fail to meet criterion 4 above. Furthermore, we can rule out another 50% (297) of the remaining 593 untested drug targets because they are unlikely to deliver new drugs for the same fundamental reasons.
首先，假设我们测试过的所有靶点中的50%可以形成至少一种获批的药物，而另外50%则无法形成任何药物，因为作用机制方面的根本性的原因（例如，安全性）。鉴于我们已经针对672个靶点开发出已获批的药物，可以推测，相似数量的靶点也已被我们完全测试过，但却没有形成任何药物，所以，我们可以把它们排除掉，不再作为潜在的新药靶点，因为它们既不新，又无法满足上述的条款4。不仅如此，我们还可以另外再把剩余的593个靶点中的50%（297）个排除掉，因为它们也不太可能去形成新药，理由同上。
Now we are left with only 296 potential drug targets, but how many of these will produce drugs that are commercially viable? It has been estimated that only about 25% of new approved drugs manage to fully recover their own R&D costs and make any commercial return. Many of those that fail commercially are me-too drugs that compete for the same drug target, but many are also novel first-in-class drugs that compete with other drugs acting by different mechanisms to target the same disease, or that target diseases with insufficient clinical need.
现在，我们只剩下296个潜在的靶点，但是，它们中有多少能够形成商业上可行的新药？据估计，只有25%的获批新药的收入能够完全覆盖其研发开支，从而获得商业上的回报。商业上失败的药物中，有很多是me-too药物，它们在同一个靶点的市场里相互竞争；但是，也有很多是创新的first-in-class药物，它们面临着和它们的作用机制不同、但适应症相同的药物的竞争；还有一些药物的适应症的临床需求不足。
So let’s assume that 50% (148) of the remaining 296 potential drug targets are not commercially viable (i.e., do not meet criterion 5 above), and we are now left with only 148 potential new drug targets, compared with 672 that we have already exploited with existing approved drugs:
所以，我们假定，剩余的296个潜在靶点中的50%（148）没有商业上的可行性（即无法满足上述的条款5），这样，我们只剩下148个潜在的新药靶点，作为对比，我们已经有672个靶点被已存在且已获批的药物所采用：
Again, this is just a rough estimate based on some crude assumptions, but still it is clear that we are rapidly running out of viable new drug targets that meet all 5 criteria above. We are literally scraping the barrel for the last remaining drug targets, and chances are we are already working on all these remaining targets in direct competition with each other. Now is it really any wonder that R&D productivity has been declining so rapidly by the Law of Diminishing Returns?
再次申明，这只是在非常粗糙的假设下做出的非常粗略的估计，但很显然，符合上述所有5个条款的新药靶点已经稀少，而我们正在高速消耗它们。我们只能在最后剩下的这些靶点里逐个地寻找机会，而且，我们也确实正在竭泽而渔，相互竞争，短兵相接。现在，还有谁仍旧怀疑研发效率因边际效益递减规律而正在高速下滑这一事实？
Limited potential impact of Pharma’s current strategies
有限的潜在机会对制药企业当前策略的影响
Given that we are rapidly running out of viable new drug targets, it is easy to see why Pharma’s R&D productivity has been declining so rapidly by the Law of Diminishing Returns. Moreover, it is easy to see why none of Pharma’s past efforts has made any difference, and why none of its current strategies will make any difference, either: They do not address the underlying issue.
鉴于我们正在高速消耗所剩无几的新药靶点，很容易看出，制药企业的研发效率正在因边际效益递减规律而高速下滑。而且，非常容易看出为什么不同药企以往的努力并没有带来什么差别，也非常容易看出为什么它们当前的策略在未来得到的结果并不会有什么差异：它们都无法解决根本问题。
Almost all of Pharma’s past and current strategies are designed to improve R&D productivity in one or more of the following ways:
几乎所有的制药企业以往及当前的策略都是用下述方法中的一种或多种来提升研发效率：
1. Increase the efficiency by which we identify viable new drug targets that meet all 5 key criteria listed earlier
2. Increase the efficiency by which we identify safe and effective new drugs against those targets identified in 1 above
3. Increase the quality and expected commercial value of those drugs identified in 2 above
1. 通过筛选出同时满足上述所有5项条款的新药靶点来提升效率
2. 针对符合第1条的靶点，通过识别以此为靶点的新药的安全性和有效性来提升效率
3. 提升符合第2条的药物的质量及其期望商业回报
For example, molecular biology, genomics, proteomics and bioinformatics have been developed to increase the efficiency of target discovery by improving our understanding of human biology and disease, while other technologies like rational drug design, cheminformatics, combinatorial chemistry and high throughput screening have been developed to increase the efficiency of drug discovery by exploring new chemical space. Meanwhile, open innovation and in-licensing have been developed to source new drugs and technologies more efficiently than internal innovation. Precision medicine with biomarkers and real-world evidence has been developed to increase the clinical benefit and commercial value of new drugs in specific patient populations. Now there is a big push with big data, machine learning and AI to make significant improvements in all these areas. And of course, continuous improvement has been Pharma’s favorite long-term strategy to improve overall efficiency.
例如，分子生物学、基因组学、蛋白质组学和生物信息学已经发展起来，通过提高我们对人类生物学和疾病的理解来提高靶点发现的效率，而其他技术，例如合理药物设计、化学信息学、组合化学和高通量筛选也已经发展起来，通过探索新的化学空间来提高药物发现的效率。同时，开放式创新和授权引进也已发展起来，相较内部创新，它们有助于提升获得新药和新技术的效率。基于生物标志物和现实证据的精准医疗也已经发展起来，这可以为特定患者群提供临床效益，从而提升新药的商业价值。现在，在所有这些领域里，大数据、机器学习和人工智能都对提升效率有巨大的推动作用。当然，持续渐进的提升也一直是制药公司所偏好的提高整体效率的长期策略。
Note that none of these strategies can increase the overall number of viable new drug targets that meet the 5 key criteria above. Instead, they are simply designed to exploit the remaining pool of viable new drug targets more efficiently, which ironically, will only accelerate its depletion.
注意，没有哪一项策略能提升满足前述5项关键条款的可行新药靶点的数量。相反，它们的目标却是提升挖掘剩余可行新药靶点的资源的效率，具有讽刺意味的是，这只会加快其枯竭的速度。
These strategies have not worked, and will not work, because they do not address the underlying issue: We are rapidly running out of viable new drug targets that can be targeted by classic small molecule drugs or large therapeutic proteins.
这些策略并没有奏效，也不会奏效，因为它们无法解决根本问题：我们正在高速消耗所剩无几的新药靶点，这些靶点可以被经典的小分子药物或大的治疗性蛋白质所靶向。
So how can we address this problem to improve R&D productivity?
那么，我们该如何解决此问题来提高研发效率呢？
An alternative approach to improve R&D productivity
一条提升研发效率的替代路径
Ultimately, the only way we can break free from the Law of Diminishing Returns is to increase the number of viable new drug targets; and the only way we can do this is to remove or relax at least one of the 5 key criteria listed earlier.
最终，我们摆脱边际效益递减规律的唯一途径是增加可行的新药靶点数量; 我们实现这一点的唯一方法是去掉或放松前述的5项关键条款中的至少一项。
At first, it seems that all these criteria are absolute critical requirements for any new drug target. For example, if there is no clear link with human disease, or if there is no clear unmet need, then there is no viable drug target. Furthermore, if we have already tested a drug target and it failed for safety reasons, or if we have already fully exploited it with existing approved drugs, then we cannot exploit it further. And finally, if we can’t hit a specific drug target with small molecules or large proteins, then we can’t develop an effective drug against that target.
初看上去，所有这些条款似乎都是任何新药靶点都需要满足的绝对关键的要求。例如，如果与人类疾病没有明确的联系，或者如果没有明显的未满足的需求，那么这就不是可行的靶点。此外，如果我们已经测试了某个靶点，并且由于安全性而失败，或者如果现有已批准的药物已经充分利用了该靶点，那么我们就无法继续开发它。 最后，如果我们不能用小分子或大的蛋白质靶向特定的靶点，那么我们就无法开发靶向该靶点的有效药物。
Or can we? Are we really limited to using small molecules and large proteins as drugs to target specific proteins and treat diseases more generally?
我们真的不能吗？我们真的仅限于用小分子和大的蛋白质作为药物去靶向特定的蛋白质来治疗疾病？
Small molecules have the great benefit that they can penetrate cell membranes to reach potential drug targets within the cell, but on the other hand, they require a clear binding pocket within the target protein, otherwise they have the wrong size and shape to bind effectively and specifically to flat protein surfaces. Meanwhile, large therapeutic proteins such as antibodies can form much stronger, more specific interactions with such flat protein surfaces, but they are generally unable to penetrate cell membranes and get into the cell. Thus by limiting our potential drug repertoire to small molecules and large proteins, we are effectively limiting our pool of potential new drug targets to extracellular proteins, or intracellular proteins that have a clear binding pocket. At the moment, we have no means to target intracellular proteins that have no clear binding pocket, yet there are thousands of these “undruggable” proteins encoded by the human genome.
小分子可以穿透细胞膜以进入细胞内潜在的靶点，但另一方面，它们也需要在靶蛋白内有一个清晰的、可以结合它的“口袋”，否则，它们的大小和形状就与“口袋”不匹配，从而无法有效地结合，特别是扁平的蛋白质表面。同时，诸如抗体等大型的治疗性蛋白质可以与这种扁平蛋白质的表面形成更强烈、更特异的相互作用，但是它们通常不能穿透细胞膜并进入细胞。因此，这把我们的潜在药物库限制在小分子和大的蛋白质的范围内，潜在的新药靶点要么是细胞外蛋白质，要么是具有清晰结合“口袋”的细胞内蛋白质。目前，我们没有办法去靶向没有明确结合“口袋”的细胞内蛋白质，但人类基因组编码了数以千计的此类“不可成药”的蛋白质。
According to the Human Protein Atlas, 3,131 (about 16%) of all proteins encoded by the human genome are “undruggable” proteins that have a clear link with disease, but can’t be targeted with either small molecules or large proteins because they are intracellular and have no clear binding pocket. This compares with only 1,937 druggable targets, of which 672 have already been fully exploited with existing approved drugs, and perhaps only 148 remain viable as explained above. Therefore, we could potentially increase the total number of viable new drug targets by as much as 20 fold, if only we could find an effective way to target them. So how can we do this?
根据《人类蛋白质图谱》，人类基因组编码的所有蛋白质中有3,131种（约16％）与疾病有明确关联，但却“不可成药”，因为不能用小分子或大的蛋白质去靶向，因为它们在细胞内，又没有清晰的结合“口袋”。相比之下，只有1,937个“可成药”的靶点，其中672个已经被现有获批的药物所充分利用，并且可能只剩148个可行的靶点尚未被利用，如上所述。因此，如果我们能够找到有效的方法来靶向它们，我们可能会将可行的新药靶点的总数量增加20倍。那么，我们该如何做到？
First, it is clear that small molecules do not have the size and shape required to bind effectively and specifically to large and flat protein surfaces. They are simply unable to compete with the tight and specific binding that occurs between different protein molecules within the cell, which is why we have never been able to develop an effective small molecule inhibitor of any known protein-protein interaction. Therefore, we are forced to use large molecules in order to compete effectively with these strong interactions, but this leaves us with the other problem: How to get such large molecules into cells in the first place?
首先，很明显，小分子不具备有效且特异的结合大而平坦的蛋白质的表面所需的大小和形状。它们也竞争不过细胞内不同蛋白质之间的紧密而特异的结合，这就是为什么我们从未开发出任何对已知的蛋白质-蛋白质之间的相互作用有效的小分子抑制剂。因此，我们不得不使用大分子来与这些强烈的相互作用有效竞争，但这留给我们另一个问题：首先如何让这些大分子先进入细胞？
If only we could find a reliable way to get large molecules into cells, then we could potentially target thousands of different proteins and protein-protein interactions that are currently beyond reach within the cell. So again, how to achieve this?
如果我们能找到一种可靠的办法来让这些大分子进入细胞，那么我们就潜在地有数以千计的不同蛋白质去靶向这些蛋白质-蛋白质之间的相互作用，但现实却是我们还无法进入细胞内。那么又是这个问题，如何达到这一目标？
The cell membrane is notoriously difficult to penetrate, especially by large molecules, but nature has shown that it can be done. For example, several large macrocyclic antibiotics and bacterial toxin proteins are known to cross the cell membrane. So can we adapt these molecules to act as drugs once they get into the cell? Or better still, can we understand how they get into cells in the first place and apply these principles to design a whole new class of cell-penetrating therapeutic proteins that could be adapted to bind tightly and specifically to any target protein in the cell? I have my own specific ideas that I would like to pursue in this regard, but hopefully it is clear by now that getting large molecules into cells is perhaps the only way to address the real underlying issue of declining R&D productivity. This problem is too important to rely on just one idea, so we need to pursue as many potential solutions as possible, in order to reverse the decline in R&D productivity and save the industry from terminal decline, before it is too late.
细胞膜非常难以穿透，尤其是大分子，但大自然表明这可以完成。例如，我们已知有几种大型的大环抗生素和细菌毒蛋白可以穿过细胞膜。那么，我们是否可以改变这些分子，让它们进入细胞后产生药效？或者更好，我们是否可以先理解它们是如何进入细胞的、然后应用其原理去设计出一类全新的穿透细胞的治疗性蛋白质、它们能与细胞内的任意靶蛋白紧密且特异地结合？在这方面，我有自己的具体想法，也在此领域有所追求，但希望现在可以明确，让大分子进入细胞可能是解决研发效率下降这一真正根本问题的唯一途径。这个问题太重要了，不能仅仅依靠这一个想法，所以我们需要尽可能多地寻求解决方案，以扭转研发效率的下降，并在致命的衰退之前挽救行业，以免为时已晚。
In summary, Pharma R&D productivity is declining by the Law of Diminishing Returns because we are rapidly running out of viable new drug targets that can be intercepted by small molecules or large proteins. None of Pharma’s past or current strategies to improve R&D productivity has worked because they do not address the underlying issue, and the only way to solve this problem is to develop completely new modalities that can address currently “undruggable” targets within the cell.
总之，制药企业的研发效率正遵循着边际效益递减规律而下降，因为我们正在快速消耗为数不多的、能通过与小分子或大的蛋白质相互作用而起效的可行新药靶点。制药企业以往或当前的策略都无法提高研发效率，因为它们没有解决根本问题，解决这个问题的唯一方法是开发全新的模式，以利用目前细胞内“不可成药”的靶点。
It is still not too late, but time is running out very fast.
现在仍然还不算太晚，但时间正在快速流逝。
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