The Future of Pharmacology Flashcards

1
Q

Learning outcomes

A

To describe the difference between ‘post-science’ and ‘anti-science’
ways of thinking.

 To identify five major current challenges in pharmacology research:
time factor, current gaps in knowledge, animal model limits, genetic variability, and the replication crisis.
 To describe five major positive future directions in pharmacology:
artificial intelligence (AI), illegal drugs being adapted for medical use, understanding the human genome, reviving older drugs, and right-to-try legislation.

 To describe the benefits and risks of ‘Citizen Science’ in pharmacology – shared data, shared molecules, crowdfunding, adverse effect reporting, and volunteering for research.

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2
Q

Today’s lecture

A
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3
Q

How it works –
and it should
be replicable

A
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4
Q

What is the scientific method?
A quick reminder from Week 1

A

 The ‘scientific method’ consists of
 organised efforts
 to come up with explanations of nature,
 always modifying and correcting these
 through systematic observations

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5
Q

Anti-science and post-science

A

‘Anti-science’ – suspicion of the very
concept and process for various
reasons, eg. science itself is part of
patriarchy, capitalism.

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6
Q

Anti-science and post-science

A

‘Post-science’ – science is simply one
discourse through which we can
interpret phenomena.

Science is one interpretative framework of many, all of which are equally valid (like post-modernism).

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7
Q

Why do people believe anecdotes but not data?

A

 1980s explosion in complementary
therapies.

 Second generation of ‘skeptics’ -
who aren’t skeptical at all.

 Are we – consumers – driving these
changes because this is what we
WANT to hear/believe?

 Internet echo chambers!

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7
Q

Anti-science and post-science

A

Both forms have similarities:

Suspicion that the science info chain has been completely compromised by financial interests, eg. drug companies, vested interests.

Seeks ‘pure’, ‘independent’ sources of information – but is rarely as critical of these sources.

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8
Q

The balance sheet

A

We’ve spent quite a lot of time in this unit showing you how using the scientific method has:

 sped up and refined drug innovation,

 produced much more effective treatments,

 made many drugs much more low-cost and accessible, and

 made it possible to share those drugs with more people than ever before in history.

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8
Q

A ‘loyal opposition’?

A

 1960s counterculture and legitimate critiques of medical establishment.

 Critics such as Ivan Illich, Thomas Szasz, and R D Laing helped to bring about many improvements in modern medicine and psychiatry.

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9
Q

A ‘loyal opposition’?

A

COVID-19 ‘cures’ belong to a rich tradition of folk medicine.

 The origins of some modern medicine can be found in folk medicine – but it’s the beginning
point, not the end point.

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10
Q

The balance sheet

A

This has come with a downside as well:

 a powerful biomedical voice that dominates treatment, eg. the overmedicalisation of normal human emotional states,

 profit-driven production and priorities, eg. pricing some drugs out of access.

 hard-to-track side-effects once a drug is released into the wider community,

 over-use issues, eg. antibiotic resistance.

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11
Q

The balance sheet

A

Mistrust of Big Pharma makes it easier for people to reject the benefits of modern drug therapy and pursue what look like safer, gentler alternatives.

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12
Q

Belle Gibson

A

Belle Gibson – young Australian woman with online profile as
cancer sufferer.

 Had launched The Whole Pantry mobile app in August 2013, at
age 21.

 Reportedly downloaded 200,000 times within its first month.

 Voted Apple’s Best Food and Drink App of 2013.

 By early 2015, the Whole Pantry app and book had made over $1
million.

 Gibson chronicled her battle with cancer on a blog of the same
name.

 Managed her cancer treatment and recovery with whole foods.

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13
Q

Real-life implications of this

A

The rise of the ‘Wellness Entrepreneur’: Belle Gibson,
Gwyneth Paltrow, Pete Evans, Elle Macpherson

 Coronavirus ‘cures’

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13
Q

Belle Gibson

A

Gibson modelled her own story and career on a nowdead ‘cancer influencer’ called Jess Ainscough -
but Gibson never had cancer.

 2017: Found guilty of misleading and deceptive conduct and fined $400,000 - still unpaid in 2023.

 Some individuals claim to have ceased their cancer treatment and relapsed after following Gibson’s advice.

 ‘Bad Influencer: Belle Gibson and the Great Insta-Con’ (BBC, July 2021, 06:20) - https://youtu.be/WYBcTGpYKIM

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13
Q

Gwyneth Paltrow

A

 2018: Paltrow’s merch site Goop was fined US$145,000 for
unsubstantiated marketing claims:

o Jade and rose quartz eggs for vaginal insertion – claimed
that they “balance hormones, regulate menstrual cycles,
prevent uterine prolapse, and increase bladder control.”

o Inner Judge Flower Essence Blend: claimed to prevent depression.

 Goop paid fine and offered refunds to customers.

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14
Q

Elle Macpherson

A

Formerly in a relationship with Andrew Wakefield of MMR vaccine
infamy.

 2010: Claimed that she consumed rhino horn products to maintain
her health and appearance (endangered species).

 2015: Promoted ‘alkaline body’ as cure-all.

 2024: Claims to have had breast cancer but refused conventional
treatments - now claims to have healed holistically.

 “I realized I was going to need my own truth, my belief system to
support me through it. And that’s what I did. So, it was a wonderful
exercise in being true to myself, trusting myself and trusting the
nature of my body and the course of action that I had chosen.”

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14
Q

Pete Evans

A

Celebrity chef and paleo diet advocate.

 May 2021: fined almost $80,000 over alleged unlawful advertising of wellness products.
 Therapeutic Goods Administration (TGA) issued six infringement notices to Peter Evans Chef Pty Ltd:

 ‘BioCharger’ device - $15,000 light machine which Evans incorrectly claimed could cure the
“Wuhan coronavirus”.

 hyperbaric oxygen therapy chambers.

 Advertising “contained statements that implied the products were endorsed by a health professional”.

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15
Q

The slowdown
of drug
development

A

 Since 2017, only 12 antibiotics have been approved worldwide, 10 of
which belong to existing bacterial classes with established antibiotic
resistance.

o On average, antibiotic resistance is developed to new market entrants just 2-3 years post-market entry.

 Average time-to-market for a new drug is 12 years.

 Failure rates are as high as 90%.

 Average R&D costs of US$1.1 billion twenty years ago have soared to US$4.4 billion.

 More new drugs are not effective and have had to be removed from
the market.

 And yet drug approval processes have sped up in the last thirty years.

 https://ideas.newsrx.com/blog/why-drug-development-is-slowingdown-and-what-to-do-about-it

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15
Q

Natural cures
for COVID-19

A

 COVID-19 is a nasty bug.

 What’s wrong with people trying to cure it themselves with natural
products?

 Nothing. It’s perfectly legal to do this.

 You could also use a range of natural products and techniques for
symptom reduction and to make you feel better.

 There is no cure for the common cold for a reason: it’s a virus that
rapidly mutates (like coronavirus).

 2017 article: https://www.theguardian.com/news/2017/oct/06/whycant-we-cure-the-common-cold

 And the common cold might protect you from COVID19! https://theconversation.com/the-common-cold-mightprotect-you-from-coronavirus-heres-how-158461

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16
Q

Problems start …

A

… when you manufacture ‘treatments’ or ‘cures’
and market them without proper evidence and regulation.

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16
Q

Is Big Pharma part of the problem?

A

 We need to look more closely at the marketing models in large pharmaceutical companies
.
 Is novel drug development dis-incentivised by them?

 Companies emphasise marketing and defending existing blockbuster products: eg. The Pill, Valium, Prozac.

 Drug companies spend only 1.3% of revenues on discovering new chemical entities, compared to
25% on promotion.

 Pharmaceutical companies shape the drug development market by investing in therapeutic areas with the largest markets and profit margins.

 A drug that treats one rare form of cancer cannot generate profit like a drug that treats headaches, sneezes, low grade blahs, etc.

17
Q

Problems start …

A

 May 2020:TGA issued fifteen infringement notices totalling
$37,800 to a doctor in Perth, including alleged unlawful
advertising of therapeutic goods in relation to COVID-19.

 June 2020:TGA issued 12 infringement notices totalling
$151,200 to MMS Australia for alleged unlawful advertising of Miracle Mineral Solution for COVID19.

 July 2020: TGA issued five infringement notices totalling
$63,000 to Victoria-based company, SGC Products Pty Ltd for
alleged unlawful advertising of products in relation to COVID-19.

17
Q

Current challenges in
drug development

A

1) Time factor: Lengthy, complex, and costly process with poor outcomes and regulatory delays.

2) Limits to our knowledge: We still don’t really understand the pathophysiology of many
disorders.

3) Animal models can only take us so far.

4) There’s a lot of genetic variability between humans.

5) Can we still rely on published data? The replication crisis.

18
Q

Publication, peer review, and trust

A

For most of the history of peer reviewed science, journal papers were accepted on trust.

 Peer review was always mostly about checking:

 consistency with the current literature

 overall quality, written expression

 whether the tables and numbers add up

 whether it makes the point it was going to make, etc.

18
Q

The replication crisis

A

 In 2011 a group called the Open Science Collaboration attempted
replication of 100 psychology experiments all published in 2008.

 They successfully replicated 35.

 Led to the following innovations:

o Pre-registration of a study: this allows us to see what the original plan is and how much of it makes it to publication.

19
Q

Publication, peer review, and trust

A

Peer reviewers offer ‘helpful’ and ‘constructive’ comments to improve the quality of the article.

 They did NOT replicate the experiments or re-run the statistical
analyses.

 They have not historically had access to the raw data sets from a paper.

20
Q

AI and drug development - good

A

The model picked out one molecule with a chemical structure different from any existing antibiotics and low toxicity to human cells.

 In laboratory tests, the drug killed many problematic disease-causing bacteria, including resistant strains.

 Halicin (named after the onboard computer from 2001: A Space Odyssey)has been previously investigated as possible diabetes drug.

 In silico screening!

20
Q

The replication crisis

A

o Registered report = you must publish, no matter what findings you got!

o Pre-prints = early release versions for anyone to comment on before the final version is published.

o Shared data sets = anyone can run your data and ideally get the same
results.

 RetractionWatch – a great website if you’re interested in science
scandals! - https://retractionwatch.com/

20
Q

Future of
pharmacology
research

A

 What sorts of options does AI offer for drug development?

 Can we make better use of ‘illegal’ drugs as therapeutics?

 Can we revive old drugs from the past that we stopped using because we developed ‘better’ new
ones?

 What about right-to-try legislation?

 Exploring human genetic variations

20
Q

AI and drug development - bad

A

AI can be scarily powerful in drug development – for evil as well as
good.

 In 2020 Collaborations Pharmaceuticals developed a presentation for an international conference on chemical and biological weapons.

 They used their AI-based MegaSyn software to generate a compendium
of toxic molecules.

21
Q

How is halicin
performing in
drug trials?
(pre-clinical)

A

 Zhang et al (2024), Safety and efficacy evaluation of halicin as an effective drug for inhibiting intestinal
infections, Frontiers in Pharmacology

 https://www.frontiersin.org/journals/pharmacology/
articles/10.3389/fphar.2024.1389293/full

 Boog et al (2021), Assessment of the antibacterial efficacy of halicin against pathogenic bacteria,
Antibiotics

 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC869
8312/

21
Q

AI and drug development - bad

A

The team ran MegaSyn overnight and found 40,000 substances, including not only VX (“venomous agent X”) and other known chemical weapons, but many completely new potentially toxic substances.

 They used some programming, some open-source data, a 2015 Mac,
and less than 6 hours of machine time.

 Many molecules may be toxic but cannot be developed into effective
weapons – but some could.

21
Q

AI and drug development - good

A

 In 2020, AI programming at Massachusetts Institute of Technology (MIT)identified a powerful new antibiotic compound.

 The researchers designed their model to look for chemical features that make molecules effective at killing E. Coli.

 Started with about 2,500 molecules, including about 1,700 FDA-approved drugs and a set of 800 natural products.

 Then tested on the Broad Institute’s Drug Repurposing Hub, a library of about 6,000 compounds.

22
Q

AlphaFold AI

A

 AlphaFold 3 (beta version) can predict the molecular structures of different proteins in minutes.

 Trained on protein structures already found by X-ray
crystallography.

22
Q

Illegal to legal drugs

A

We know that cannabis products have some therapeutic applications.

 Psychedelics are now being explored as possible future
mainstream drug treatments for mental disorders.

22
Q

AlphaFold AI

A

 “Our lab at King’s College London used X-ray crystallography to predict a structure formed by two bacterial proteins that are loosely involved
in hospital superbugs when they interact.”

 “Previous incarnations of AlphaFold predicted the individual components but could never get the complex right – yet this new version solved it at the
first attempt.”

23
Q

Illegal to legal drugs

A

As of late 2021, esketamine hydrochloride is approved for
treatment of major depressive disorder in adults –TGA,
Australia.

o Nasal spray ‘Spravato’

o Approved for 5 years from 2021

 LSD microdosing clinical trials are underway.

 Are they working? Read and find out -
https://www.sciencedirect.com/science/article/pii/S24519022
24000156

23
Q

Reviving old antibiotics

A

Old antibiotics from the 1950s–70s still work.
 Current standards and the requirements for clinical testing have evolved over time.

 These drugs haven’t been tested by modern standards.

 Prescribing them may carry significant risks for patient outcomes, adverse events and the emergence of resistance.

24
Q

Right-to-try
and early
access
legislation

A

 US: terminally ill patients can try experimental therapies that have only completed Phase I testing in the US.

 These therapies have not been approved by the Food and Drug
Administration (FDA).

 Expanded access or compassionate use - allows people in extreme situations to try unapproved therapies.

 UK: EAMS (Early Access to Medicine Scheme).

24
Q

Right-to-try
and early
access
legislation

A

 Australia: Special Access Scheme - https://www.tga.gov.au/special-accessscheme-guidance-health-practitioners-and-sponsors

 Category A patients are defined as being seriously ill if:

 For medicines and biologicals, they have a condition from which death
is reasonably likely to occur within a matter of months, or from which
premature death is reasonably likely to occur in the absence of early
treatment.

25
Q

Pharmacogenetics -
pharmacogenomics

A

 Pharmacogenetics and pharmacogenomics: the study of
variability in drug response due to heredity (these two terms are
increasingly used interchangeably)
.
 UWA biotechnology start-up Gene S: Svetlana Baltic and Suzanna Lindsey-Temple.

26
Q

Pharmacogenetics -
pharmacogenomics

A

 Gene S has plans to develop and commercialise a TGA-approved
medical device or kit.

 This would help doctors to prescribe medication based on
genetic profiles of individual patients.

27
Q

Shared data – a way forward
from the replication crisis

A

 OpenScience - https://openscience.org/about-openscience/

 Center for Open Science - https://www.cos.io/ and the Open
Science Framework - https://www.cos.io/products/osf

 This is anathema to most big pharmaceutical companies.

 Their profits largely rely on a complex system of patents and other
legal protection of intellectual property.

 However, the future is coming …

27
Q
A
27
Q
A

Crowdfunding -
Experiment.com and the
Open Insulin Project

 https://experiment.com/projec
ts/open-insulin

 “A team of biohackers is
developing the first open
source protocol to produce
insulin simply and
economically. Our work may
serve as a basis for generic
production of this life-saving
drug and provide a firmer
foundation for continued
research into improved
versions of insulin.”

28
Q

Volunteering
for drug trials

A

 Harry Perkins Institute – Linear Clinical Research Ltd

 https://www.linear.org.au/ - paid clinical trials

 https://www.australianclinicaltrials.gov.au/- NHMRC website

 UWA’s Crowd Research page -
https://crowdresearch.uwa.edu.au/participate/

 This page has both participation and crowdfunding opportunities

29
Q

Adverse Drug
Event (ADE)
reporting

A

 This causes an underestimation of the incidence of harmful side effects.
 Slows down the discovery of new and rare phenomena, especially the
ones related to under-represented categories of patients.

 COVID-19 vaccine ADE reporting – good example.

 Scaboro S, Portelli B, Chersoni E, Santus E, Serra G. Increasing adverse drug events extraction
robustness on social media: Case study on negation and speculation. Exp Biol Med (Maywood). 2022
Nov;247(22):2003-2014. doi: 10.1177/15353702221128577

29
Q

Adverse Drug
Event (ADE)
reporting

A

 Pharmacovigilance (PV) – activities relating to the detection, assessment,
understanding and prevention of adverse effects or any other medicine/vaccine related problem after drugs enter the market.

 The global pharmacovigilance technology market is forecast to grow
from $7.8 billion in 2022 to $17.36 billion in 2030.

 Traditionally, ADE reports are collected through the communication between patient, healthcare provider, and PV authorities.

 However, over 90% of the ADEs reported by patients are not forwarded to local or regional PV systems.

29
Q

ADEs and social media

A

 Increasing number of internet users are sharing their

ADEs on the Internet – forums, Facebook, Twitter.

 These sources can potentially provide an updated stream of user feedback on medications through
information mining.

 BUT: This data is very noisy = unstructured and hard
to mine.

30
Q

ADEs and social media

A

Social media texts contain colloquial language, typos, slang, metaphors, and non-standard syntactic constructions.

 Applying AI to real-world data from various sources such as AERs and social media could speed things up.

 In the meantime, can we do anything to help?

31
Q

Case study:
Mirena in
France, 2017

A

 Mirena is a commonly used hormonal contraceptive IUD
(intrauterine device).

 In France, there was a media expose about potential adverse side
effects of Mirena - around 15 May 2017.

 Before this, 510 AEs had been reported for Mirena in France, three
quarters of which came from health professionals.

 After the media expose, 2714 AEs were reported, 99% of which
came from patients.

 This is much richer data and is useful for further research and
testing of Mirena to make it safer.

32
Q

How to report adverse drug events – including COVID-19 vaccines!

A

 See your health professional
 Make a report yourself

32
Q

And one more
thing …

A

 You can always do Pharmacology at UWA as a major!

 You can have a go at changing the world through the fast-paced and rapidly-changing world of drug discovery.

 Ricky would love to talk to you about all this!

33
Q

Summing up

A

 There are some real challenges for the future of pharmacology and new drug development.

 Anti-science and post-science perspectives are an important part of our current scientific discourse.

 They are sometimes useful as a ‘loyal opposition’ to help keep mainstream pharmacology honest.

 However, these beliefs have real life implications for health care and prevention of disease.

 We can ALL do things to improve the quality of research and discourse around drug use and development.