Future of Pharma and health care in an AI world. How COVID and AI accelerated pharma innovation,drug discovery, clinical trials, safety tests, regulatory approval, licensing. Impact on future drug development and future health care. Pharma keynote speaker

Futurist Keynote Speaker: Posts, Slides, Videos - Future Health Care and Pharma Keynote Speaker

COVID forced acceleration in pharma drug discovery, pharma innovation, clinical trials and regulatory approval / licencing as well as major changes in delivery of health care. What does this all mean for the future of pharma and health care? Especially when combined with pharma impact of AI / Artificial Intelligence on drug discovery and clinical trials. Take for example the rapid growth of "virtual drug trials" - see below.

* "How AI Will Change Your Life - A Futurist's Guide to a Super-Smart World" - Patrick Dixon's latest book on AI is published in September 2024 by Profile Books. It contains 38 chapters on the impact of AI across different industries, government and our wider world, including impact of AI on future Pharma, AI and Pharma innovation, AI in drug discovery, AI to accelerate clinical trials and regulatory approval.

Huge acceleration in pharma innovation, drug discovery, clinical trials and regulatory approvals

As a Physician as well as a Futurist I have worked with most of the largest pharma companies, helping them to understand the future. I warned for over two decades of global risks from new pandemics like COVID, and also predicted huge global opportunities in AI.

So what will be the Future of Pharma beyond COVID, in a pharma world increasingly dominated by AI?

Here are notes on a recent Virtual keynote on the future of pharma.

Normal pace of pharma innovation / drug development far too slow for COVID

For years I had been saying that pharma innovation was too slow - indeed that issue added to the global crisis during the COVID pandemic.

The largest 15 pharma companies spend typically $100bn out of the global total on pharma research and development, yet discover only 20% of new drugs.

80% of early drug discovery and Phase I/IIa clinical trials are carried out by much smaller biotech companies, or smaller pharma collaboration with Universities for example.

Last-century clinical trial methods had to change fast for COVID

A huge problem is funding the gap between early work and reaching the stage where a potential drug gains attention of big pharma. So many great therapies get abandoned at this exciting stage, full of promise, but unable to find a sponsor.

And a major reason for that has been the inefficiency of drug trials and prohibitive cost of trying to get a drug to regularity approval.

COVID has called a lot of that last-century methodology into question.

And Artificial Intelligence (AI) has already started to transform every aspect of pharma / drug development with wider impacts across future health care.

COVID forced new models of collaboration and use of AI / Artificial Intelligence in pharma

Pharma innovation is also often slowed down by squabbles over who owns IP / knowledge.

Not only that, most published research is hidden behind expensive firewalls online - available only on subscription or expensive pay-to-view arrangements, both totally beyond the budget of researchers amongst 85% of the world's population who live in emerging markets.

Expect this to become a major ethical issue - we have to find a more equitable way to solve health problems, for the sake of the whole of humanity.

The good news is that COVID forced scientists and entire companies to work together across the world for the common good. The same happened with HIV / AIDS.

And that has massively accelerated progress against COVID - for example the genome of the virus was shared by the Chinese within days of decoding, and similar sharing has happened many thousands of times since.

And of course, once such data sharing was opened up, new AI / Artificial Intelligence analytics tools could then be used to maximum effectiveness.

AI / Artificial Intelligence helped accelerate development of COVID vaccines and therapies

AI accelerated development of COVID vaccines. The key was using Artificial Intelligence to help predict what kind of molecules would be most likely to stimulate the immune response against a wide number of COVID variants. Such AI pharma tools are now used widely in drug discovery / early stage pharma research, across the world.

AI was also used to help predict clinical outcomes, for example for COVID patients on ventilators in intensive care units.

Artificial Intelligence was also used to develop treatment plans, propose optimum therapy combinations and so on. A large number of scientific research papers were published during the pandemic on the use of Artificial Intelligence in pharma research and health care.

AI was used to predict when different phases of the pandemic would peak, calculate transmission rates and predict likely impact of new COVID variants on global health.

COVID forced early research results to be made available in a transparent way

For a host or reasons including worries about share price manipulation, drug trial data owned by a particular pharma company is regarded as highly sensitive and confidential.

So we often don't hear about early stage failures in the lab, and we often only hear after some months about promising lab results.

Many scientific journals hate it if what they are being asked to publish (and give authority to) has already been "leaked" to the press - indeed they may often refuse to publish if that happens.

COVID pandemic forced a different approach to private knowledge

It is in the interests of humankind to make known what is known privately, to the whole research community, so that action can be taken immediately, building on what different teams are discovering.

And also to enable clinicians to make early treatment decisions, particularly if there are signs that existing, low cost, widely available drugs may have an impact on survival rates of COVID infection.

This was not just important during COVID, but for the longer term, enabling faster drug development and more lives to be saved.

New funding models for global research / collaboration

Of course this also meant different funding models.

We saw this in the past with HIV / AIDS where institutions like the Bill Gates Foundation agreed to fund the research in pharma labs, on condition that their results were made available to all humankind, with manufacturing and distribution then outsourced on a commercial basis to pharma companies.

And there has been pressure on companies with effective vaccines to make them available globally at cost. That may sound very unfair on shareholders, but there is huge benefit to the brand through favourable media coverage.

I the research is on drugs that are already well-known and widely available from multiple companies off-patent (see below), then the results are less contentious.

On the there hand it can also mean that no company cares much any more about getting the good news out about that "old drug" to clinicians.

COVID is just one viral threat - expect many more

Pharma can't just go back to normal before COVID, whatever that was anyway. For the last 20 years I have warned repeatedly of risks from new viral pandemics like CVID. Here are a few from the last couple of decades:

2003 - SARS with 10% mortality rate

2003 - Bird Flu with 60% mortality rate

2009 - Swine Flue with 0.02% mortality rate - but infected 50% of world's children in 12 months

2012 - MERS with 34% mortality rate

2019 - COVID-19 with 0.5-1% mortality rate

So we need to completely rethink our approach to vital threats.

We cannot allow our world to be held to ransom by new viruses

With radical innovation - see below - pharma companies have reduced development time from 4 years minimum for any new vaccine to less than 8 months, including initial safety and impact testing, but it will still be a gigantic effort to vaccinate the whole world.

And even if we can do so with vaccines, it will take a year to know if the vaccine protection against that particular virus type / variation actually lasts a year. Two years to prove two years protection, five years to prove five and so on.

Huge risk from new COVID variants

All the while, new variants can be generated that evade the vaccine to one degree of another.

To be precise: for every 100 million infected we are seeing 3-5 major new variants. But by March 2021, over 7.5 billion human beings had not been infected, nor had received a vaccine.

Do the maths. That's why it is in all our interests that every nation is enabled to tackle COVID effectively and rapidly, regardless of their own wealth and health care infrastructure.

Yes of course we need vaccines, mainly to buy humanity time until we can sort out better ways to deal with this global menace.

Truth is that the real answer to COVID etc is better antivirals

A fair better solution in the longer term is finding a wide range of much more effective antivirals.

The best antiviral we have today is far less effective against viruses than penicillin was as an antibiotic when first discovered.

That is the shocking truth.

If a child is taken to hospital with bacterial meningitis or bacterial pneumonia for example, chances are the doctors will administer a drip of high-dose antibiotics and the child will be home rapidly.

But if the cause is viral, the same doctors will have almost nothing to offer other than general supportive to to try to keep that child alive until his or her own immune system begins to do it's work.

Indeed, the desperate lack of progress in antivirals over the last 80 years is directly responsible for the severity of the COVID crisis in 2020-2021.

But then it has to be said that even antibiotic research has progressed at a snail's pace.

The last major breakthrough back in the 1960s - one reason we have so many issues today with multiple resistant bacterial infections - a major global risk to the future of health care.

That is the reason why we can expect a gigantic push into antiviral research by pharma companies large and small.

Why has antiviral research been so neglected?

The reason is that it is so hard to make money from treating a condition that gets completely better very quickly. (And most viral diseases are considered to be trivial, while we vaccinate against many of the rest.)

That is why so much pharma research is committed to drugs that have to be taken every day for life.

But such drugs of course are not cures, just suppressors in many cases.

Examples include medication for blood pressure, or asthma, or high cholesterol, or rheumatoid arthritis. Such drugs are not altering in any permanent way the fundamental problem

1400 clinical trials in progress against COVID by early 2021

Before COVID, many pharma companies had already developed labs which could test hundreds or even thousands of new compounds every month.

And the combined power of all that has been massively ramped up with over 1400 clinical trials for COVID treatments by mid March 2021, as a result of identifying tens of thousands of promising molecules.

The key of course is co-ordination rather than 100 companies all testing similar substances.

It can start pre-lab, by using Artificial Intelligence to map out what shape molecule might fit certain receptors or block certain processes, sharing that knowledge widely, and then different teams using special techniques to make it, and see if it really does work.

Testing ten thousand candidate drugs at a time

But most such testing is a massive conveyor belt: dipping a drop or two of thousands of well-known existing compounds, or drugs already in development, or in clinical use, into flasks containing human cells which have just been exposed to COVID-19 virus, to see what happens.

And if there is evidence of benefit, then trying the same molecule on animals who are susceptible to COVID-19 (a huge number of mammals) or animals such as mice that have been altered in some way, for example with implanted human lung tissue, to try and see more accurately what might happen in human beings.

So all of these mass-screening techniques have been hugely expanded, and this capability will speed up every future search for effective therapies in other conditions over the next decade.

Big Data analysis of people who become ill - more common in future

Many nations have encouraged millions of people to download COVID-19 Apps on which potential early symptoms of COVID-19 can be reported and other things such as location, as part of contract tracing.

But other information is being collected at the same time on many of these - such as medications being taken routinely, other medical conditions, age, gender, ethnicity, occupation and so on. This is a gold mine for future research.

As a result of this kind of Big Data analysis, we have been learning very rapidly of all kinds of potentially important associations.

For example, Big Data analysis suggested that people who wear glasses, or take low dose aspirin, or take particular types of asthma inhalers, or have young children at home, may have lower risks of COVID infection (glasses protect eyes, and cross-immunity from common colds caught from young children), or lower risks of secondary blood clotting (aspirin) or lower risks of immune over-reaction in the lungs (inhaled steroids).

A hundred thousand other useful discoveries await being made for other medical conditions as a result of this kind of analysis, especially when combined with past medical records and gene analysis.

Predictive Analytics to change medical prescribing

over 400,000 people die in the US each year from avoidable medical errors, mainly caused by prescribing errors. Not just too high or too low dosages but also lethal combinations of drugs with combined toxic side effects.

Expect huge growth in digitally-assisted therapy decisions, with physician warnings, patient warnings, pharmacist warnings and so on, all automatically triggered, based on ever-enlarging data sets globally.

Massive acceleration of Virtual drug trials in future due to COVID

Drug trials typically cost $1.2 billion each to bring a therapy to market, but most are scrapped somewhere along the way - wonderful results maybe in the lab or in mice, and possibly some effect in small numbers of patients, but with less impact seen or more side effects, amongst larger groups.

When COVID hit, it was clear that normal drug trial methods would have to be abandoned or changed.

Patient enrolment

It can normally take five years or more to enrol a sufficiently large group of patients with the same condition, to be able to prove safety and impact.

Usually that means phone calls and letters, then face to face interviews, meetings with clinicians and so on.

But during the COVID pandemic none of that was possible without risking many more deaths from extra face to face contact, and from major delays.

So pharma companies migrated to virtual recruitment:

- Email contact

- Phone calls

- Video interviews

Providing medication

In usual clinical trials, patients are asked to attend a clinic, meet a doctor or nurse, be re-assessed each time, possibly given some medication to take home, or possibly all medication to be given by a trained health care worker.

With COVID trials, many pharma companies were forced (with regulatory / ethical approvals) to remote administrations.

So the test drug (or placebo - neither researchers or patients know what they are actually being given until the data is assembled at the end) is sent to the home of a recruit who has never been met face to face.

Patient assessments mid-trial

And video calls have turned out to be highly effective in patient monitoring, in addition to asking them to self-report side effects or any other issues via a smartphone App.

Wearables or home based diagnostics / clinical monitoring in the community

Wearable health-linked technology is already owned by the majority of adults in many developed nations - usually for monitoring exercise and so on. The capability of these sensors is improving while costs will continue to fall dramatically.

Expect 250 million people to be wearing such health devices by 2023, a $70bn a year market by 2025.

All these kind of devices have proven useful in helping to monitor patients remotely in clinical trials

Video consultations of patients instead of clinic visits

All the technology existed for Virtual consultations for over a decade before COVID struck of course. What was it that caused such resistance in clinicians to routine use of FaceTime for example or its equivalent?

As we have seen in routing health care during COVID, a single five minute video call can take a fraction of the time of a face to face home visit for the doctor, and can save lives - for example allowing instant visual assessment of the condition of a sick baby at home at night.

And so video has also become an integral part of COVID-related drug trials.

Wider impact on future health care from COVID

When you combine the impact of Big Data, predictive analytics / artificial intelligence, genetic screening, home-based diagnostics and wearables, video consultations and so on, we can see that the radical transformation of health and pharma post-COVID has hardly begun.

What is more, patients were already becoming more knowledgeable than their physicians regarding the latest published research on their conditions through Google.

But now they also may be the first to know that something is amiss.

to be alerted of a fall or rise in blood sugar, or a heart irregularity and so on.

And so most patients in future drug trials will know more than their researchers about their own drug response.

Expect huge fall in pharma costs for all of today's most expensive drugs

At the same time, we will see dramatic falls in cost of all the most expensive drugs sold today, as they fall out of patent protection.

This is independent of COVID, but an important part of the post-COVID picture in health care.

Typical would be a drug costing $100 a tablet, falling to $5 or less as a generic version - because manufacturing and distribution is usually very small part of the total price of a powerful new drug.

Most of the drug price is to try and recover the $1.2bn spent in development, cover costs of all the other drug trial failures along the way, and to make a return to the shareholders who invested in the research and took the risks.

Since most patents are only for 25 years, and most drugs take 15 years to become licensed, patent expiry is a medical fact in less than 10 years for almost all drugs in the world that are still "owned" by a pharma company.

Post-COVID expect huge growth in day-surgery and day-care

COVID forced even more clinicians to find ways to treat people as day cases and get them back into the safety of their own homes as fast as possible - bearing in mind that in many nations up to a third of new COVID infections were acquired in hospitals.

But this was just an acceleration of an existing trend - for example more than 140,000 stents (tiny hollow tubes) were inserted last year into US patients with blocked coronary arteries, most of whom went home on the same day - instead of having open heart surgery as the case two decades earlier.

In summary, expect huge, longer term changes in how pharma research is conducted beyond COVID, with faster, cheaper drug development, in the context of many ongoing shifts in health care, linked to the digital revolution.

The wider lesson is that many of the greatest innovations in future health care will not be from one discipline or speciality alone. Expect synergies between Pharma, Medtech, Biotech and Infotech for example.

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