F. E. Smith and the Future of Pharmaceuticals and Insurance

None the wiser, perhaps, my lord, but certainly better informed.
—   F. E. Smith after being told by a judge, “I’ve listened to you for an hour and I’m none wiser.

It’s difficult to predict the future without first taking a look at the past. We’re going to take that a step further by examining a vision of the future from the past, courtesy of former cabinet minister and lawyer F. E. Smith, who was a friend of Winston Churchill’s. Shortly before he died in 1930, he wrote a book called The World in 2030 ADin which he shared some predictions of what the world would look like in 100 years’ time.

To understand Smith’s views on healthcare and lifespan, it’s important to remember that he was writing at a time at which tuberculosis was one of the leading causes of death both in the United Kingdom and around the world. According to the BBC, “[Smith] was optimistic enough to suggest [that] the eradication of [tuberculosis] and other epidemic diseases were ‘fairly certain’ by 2030, as was ‘the discovery of cures for such scourges as cancer’.”

Smith also believed that we’d live longer, with scientists creating “rejuvenation” injections that could prolong our average lifespan to up to 150 years. However, the BBC explains, “[He] acknowledged this would present ‘grave problems’ from an ‘immense increase in population’. He also foresaw extreme inter-generational inequality, wondering ‘how will youths of 20 be able to compete in the professions or business against vigorous men still in their prime at 120, with a century of experience on which to draw?’”

So it seems clear that while Smith got some things right, he was drastically off the mark with others. A great example of this is his prediction that cars would be obsolete by 2030 because we’d all own private airplanes. “The man of 2030 will set off for the weekend, after his work, in a small, swift airplane, as reliable and cheap as the motor-car on which we depend today.” Other predictions were more realistic. Bearing in mind that he died 40 years before the moon landing, he was surprisingly accurate with his prediction that by 2030, the first preparations for a manned mission to Mars would be underway. Unfortunately, the BBC also says that he thought “the first ‘half a dozen’ attempts could miss the planet entirely, leaving astronauts to die onboard as they drifted further from Earth.” Someone should warn Elon Musk.

Other seemingly outlandish predictions include the survival of the British Empire, although he did suggest that the capital might shift from London to somewhere in Canada or Australia. He was also skeptical about renewable energy, predicting, “By [harnessing] tidal energy to any large extent, we should diminish the speed of the earth’s rotation. [If it’s overused], a 48-hour day is a possibility in the far future.”

Smith also predicted an increased usage of eugenics, a branch of science that’s lost favor in recent years because of its association with the Nazi party and their atrocities during the Second World War. Smith never lived to see that and so perhaps he would have changed his mind. The idea is to “improve” the human race by controlling reproduction and ultimately artificially shaping evolution. The BBC says, “He claimed a clever young man would ‘consider his fiancé’s hereditary complexion before proposing marriage’. In return, ‘the young woman of that day will refuse him because he has inherited a gene from his father which will predispose their children to quarrelsomeness’.”

Finally, Smith had a few ideas when it comes to food and pharmaceuticals, including the idea of synthetic food from laboratories overtaking conventional agriculture in order to cater to the growing population. He said, “From one ‘parent’ steak of choice tenderness, it will be possible to grow as large and juicy a steak as can be desired.” If this sounds familiar, the chances are that you’ve heard about recent advances in lab-grown meat, which supporters argue will reduce concerns about animal cruelty whilst simultaneously reducing the impact that animal agriculture has on the environment.

And as for pharmaceuticals, Smith wrote, “Should chemistry in the next hundred years be able to discover new substances as pleasant and harmless as tobacco, yet each possessing a different effect on the consumer, it will have earned the thanks of every hard-worked man and woman in the world.” It’s ironic, really, considering he died at the age of 58 after a lifetime of heavy drinking and smoking.

Smith’s vision of the future is both surprisingly prescient and as wacky as they come, but I wanted to include it here for a reason. It’s an important reminder that predicting the future is a fool’s game, and one that it’s almost impossible to win. This is especially true when those visions stretch so far into the future that there’s no chance of living to see whether the predictions pan out.

No predictions of the future can ever be 100% accurate. Nevertheless, that’s no excuse to avoid thinking about the future at all, it’s just a reminder that we should take those predictions with a pinch of salt. And with that in mind, let’s take a look at what the future might bring — personal airplanes not included.

As easy as playing with LEGO.

The Future of Pharmaceuticals

While working on my upcoming second book, I was lucky enough to be invited to contribute to PharmaBoardroom, a healthcare site that provides industry trends, news, and reports from all over the world. As 2018 turned into 2019, I was asked to write a piece predicting the future of the pharmaceutical industry, and it got me thinking.

The pharmaceutical industry is ripe for disruption. After all, it hasn’t really changed for over half a century, despite the fact that the internet and the World Wide Web have revolutionized almost every other major industry on the planet.

To understand the future of the pharmaceutical industry, we first need to understand the present. The good news is that Ingrid Torjesen has us covered in an article that she wrote for The Pharmaceutical Journey, where she explains, “Before a drug is deemed suitable for patients, it has to go through rigorous testing and cost-effectiveness analyses. Each year sees a couple of dozen new drugs licensed for use, but in their wake, there will be tens of thousands of candidate drugs that fell by the wayside. The research and development journey of those new drugs that make it to market will have taken around 12 years and cost around £1.15bn.”

The drug development journey begins when researchers undertake research to understand the processes behind a disease. This often involves identifying a gene or a protein that’s instrumental to the disease and then searching for a molecule or a compound that acts on the target. “As many as 10,000 compounds may be considered and whittled down to just 10 to 20 that could theoretically interfere with the disease process,” Torjesen says.

From there, we move on to pre-clinical testing and then clinical trials, usually consisting of phase 1, phase 2 and phase 3 trials. Each of these phases helps to weed out ineffective or unsafe drugs before they even get to the stage at which they’re submitted to the MHRA (in the UK) or the FDA (in the US) in an attempt to get a license to market the drug. “If a license is granted, that’s not the end of the process,” Torjesen explains. “In England and Wales, drug companies need more than a marketing authorization for most patients to be able to access treatment on the NHS — they also need the National Institute of Health and Care Excellence (NICE) to recommend that it should be made available through the NHS.”

From there, we move on to patenting and eventually a general release, but it’s these early steps I want to focus on today. That’s because a little thing called artificial intelligence has the potential to dramatically streamline the drug discovery process.

AI is great at processing huge amounts of data and arriving at conclusions, especially when it’s coupled with its sister technology, machine learning. It can also be used to power complex simulations that emulate real-world scenarios and give researchers a good idea of where to focus their efforts before they even get started. It can streamline the development process and save money, reducing a drug’s time to market while simultaneously cutting any risks involved in the clinical trial stage.

Let’s revisit the existing model of drug development. AI can help out right at the start by crunching the numbers and helping researchers to identify genes and proteins, as well as compounds that could potentially have an effect on them. It effectively points researchers in the right direction, acting a little bit like a satnav. It might not get it right every time, but that’s why it’ll be supervised by human oversight. In the same way that you wouldn’t follow your satnav if it told you to drive into the sea, researchers will be able to take the AI’s findings with a pinch of salt and to overrule it when needed.

AI will also be able to simulate clinical trials and even what might happen if there was a real world release and if the drug made its way into the hands of the general public. This wouldn’t replace traditional phase 1, phase 2 and phase 3 clinical trials, but it could save pharmaceutical companies money by stopping them from investing in clinical trials that are doomed to failure before they even start. These savings — as well as the inherent savings from faster, more streamlined research processes — could help to keep overheads down and ultimately allow pharmaceutical companies to sell drugs at lower prices. After all, there’ll be less of an overall investment for them to recoup.

The future of pharmaceuticals isn’t just about artificial intelligence and machine learning. For example, blockchain technology has a lot of potentials when it comes to data storage and transmission, while wearable devices could have an impact by helping patients to take control of their health and reducing the need for pharmaceuticals in the first place. I wouldn’t be surprised if Pfizer, Johnson and Johnson and other major pharmaceutical companies switch their focus to more of a preventative model in which they become software and hardware developers as well as being traditional drug companies.

But it’s an artificial intelligence that has the greatest amount of potential to bring disruption, at least in my eyes. And this holds true not only for pharmaceuticals but also for the healthcare industry as a whole. 2019 is just the beginning.