You Can Tell AI Tools Are Working And Useful When The Commercial Hardheads Adopt Ttem

This appeared last week:

Meet ChatPwC, the custom-built AI tool being rolled out at the firm

Tess Bennett Technology reporter

Feb 6, 2024 – 2.09pm

PwC Australia has given its 8400 partners and staff access to a custom-built virtual assistant – called ChatPwC – that is capable of formatting data, writing code, summarising meetings and documents, and writing emails.

Following a six-month trial with more than 1000 employees, all local PwC staff will have access to the new generative artificial intelligence tool which the firm hopes will boost productivity and the quality of client work.

Tom Pagram, PwC Australia’s artificial intelligence leader, said ChatPwC was powered by a broad range of AI models – including the ones that underpinned ChatGPT – which were trained to complete specific tasks.

“The model we use for tax might be different from the model that we use within strategy consulting,” he said.

“The generative AI landscape is moving so quickly, quite intentionally, we’re not locking ourselves into any one provider or tool.”

Professional services firms are racing to position themselves as leaders in the new field of generative AI, a technology capable of understanding and creating text, which is widely expected to reshape white-collar work.

Strict guidelines

While PwC has not blocked access to outside tools like ChatGPT, the firm has guidelines in place stating that public chatbots should not be used for business purposes or fed any firm or client data.

“We’ve had really clear and important feedback from staff that they want to be equipped with generative AI tools that they can use for work purposes,” Mr Pagram said.

During the pilot, employees and partners used ChatPwC to prepare for client meetings by conducting specialised research on topics ranging from electricity generation to primary education and superannuation.

Mr Pagram said the goal was to connect more of PwC’s data and systems to generative AI, so the virtual assistant could provide insights on a client, industry and any restrictions the firm had around providing services to them.

“The goal is to have one way for people to get answers to their questions from a really broad range of data sources and systems, rather than having to go to eight separate tools to ask a simple question,” he said.

AI output must be reviewed

Before staff can access the tool they must complete a training program and get up to speed on the firm’s AI rules.

The introduction of generative AI tools means firms will need fewer employees to complete the same amount of work and there will be fewer learning opportunities for junior staff to learn the ropes.

Mr Pagram stressed that humans would be ultimately responsible for any work produced using ChatPwC and all AI output must be “reviewed by a suitably qualified expert”.

More here:

https://www.afr.com/companies/professional-services/meet-chatpwc-the-custom-built-ai-tool-being-rolled-out-at-the-firm-20240202-p5f21q

The big consulting firms are as focussed of profitability and the bottom line as any organisation you can find and it they are deploying the evolving AI toolsets you know the benefits are real and likely to be sustained.

I see my role from this point is merely to document the rate of progress.

David.

I Keep Hoping The Day Will Come As It Would Make Things So Much Easier!

This appeared last week:

07 February 2024

To boldly diagnose: day of the tricorder is at hand

By Ivor Campbell

What used to sound like science fiction is becoming technological reality, with implications for general practice.

When two or more people from the world of medical technology meet, talk inevitably turns to the ongoing, yet elusive, search for an industry-standard, multi-disciplinary diagnostic device – the fabled tricorder. 

Fans of Star Trek will recall the small, rectangular gadget with a top-mounted, rotating hood and shoulder strap, routinely carried by Dr Bones McCoy whenever he was beamed down to a new planet. 

Simply by waving it in the general direction of stricken Starship Enterprise crew members, Bones was somehow able to diagnose anything from acute Hutchinson-Gilford Progeria Syndrome to an ingrown toenail. Of course, this was unnecessary for any crew member wearing a red shirt. 

While the Star Trek tricorder remains the stuff of science fiction, diagnostics companies globally continue to beaver away behind the scenes in search of a machine capable of diagnosing the highest number of possible conditions within a single technology. 

Visitors to global conventions like Medica and Medlab – the latter is in Dubai this week – will be aware of the now perennial beauty contest among companies showing off their latest prototypes of devices and software, aimed at facilitating multiple test capabilities. 

A decade ago, Qualcomm, the San Diego-based communications technology company offered a $US10 million prize to anyone who could produce a machine that most closely approximated the tricorder. 

The winner was Final Frontier Medical Devices, based in Paoli, Philadelphia, whose DxtER device was capable of diagnosing 13 conditions by integrating insights from clinical emergency medicine and data analysis from actual patients, using non-invasive sensors to collect vital signs, body chemistry, and biological function data. 

Since then, the march of artificial intelligence has placed booster rockets under existing technologies, to create advances that would have seemed unthinkable only a few years ago. 

Devices such as digital stethoscopes by Clinicloud and Eko Core, and one-channel ECG monitors like WIWE and AliveCor’s Kardia, reveal a focus on making diagnoses faster, more accurate, and convenient.  

The availability of multi-channel ECGs, like the ECG Dongle, and multi-sensor devices such as Viatom Checkme Pro, further demonstrate the evolution of diagnostic capabilities.  

These devices aim to streamline the diagnostic process, providing users with real-time data and promoting communication with smartphones for comprehensive health monitoring.  

Last year a team at the University of California-Santa Cruz announced it had developed a portable gadget that uses a special laser to analyse tiny particles in blood samples, to simultaneously identify multiple viruses, DNA, antibodies, and cancer markers.  

Unlike other chip-based blood test devices that focus on a single target, this technology integrates optics and microfluidic channels on a chip, allowing it to identify various particles with different concentrations.  

The device, which is being commercialised by Fluxus Inc, based in Sunnyvale, California, uses a laser beam to detect particles and adjusts its sensitivity to accurately measure both high and low concentrations.  

The researchers, led by Dr Holger Schmidt, also applied machine learning to enhance accuracy in distinguishing different particle types. The technology is being commercialised by Fluxus Inc. for medical use and holds potential for studying neurodegenerative diseases and paediatric cancers. 

The reason for the industry’s obsession with such devices is because, in the world of medical diagnostics, the pursuit of efficiency has become relentless, particularly since the covid pandemic.  

However, having a fantastic product with brilliant engineering is not enough. Cost-effectiveness and speed are crucial factors that can make or break a diagnostic device and the company behind it and, as demands on public health providers continue to mount, the significance of anything that can save doctors’ time, and the health service money, cannot be overstated.  

An ongoing review of how to triage and treat general practice patients quickly and effectively is under way in many countries around the world. The current model, in which local family doctors’ surgeries are the first port of call for patients, is seen by many people as no longer fit for purpose – not least because they don’t currently operate outside of office hours when more people now want to be seen. 

In future, it is expected that much of the burden of general practice will fall on out-of-hours clinics and local pharmacies, and that cleverer and more versatile diagnostic technologies will play an ever greater role. 

Limited shelf space in pharmacies and in confined consulting rooms creates a demand for ever more compact and multifunctional solutions, hence the search for the tricorder-like devices. 

Yet, while the physical and cost benefits of such devices are clear, there is a growing awareness that they might create new and unintended consequences for medical practitioners. 

In particular there is a recognition of the dilemma GPs face when presented with immediate and potentially life-altering information about a patient’s condition.  

The delicate balance between rapid diagnostics and allowing healthcare professionals the time to carefully analyse and plan treatment is a critical consideration. 

Part of the review’s remit is to find ways to free GPs from dealing with relatively minor and less consequential conditions that they currently spend so much time diagnosing and treating. 

Many countries have a large number of highly qualified pharmacists, with extensive pharmaceutical education, who could contribute significantly to alleviating pressures on local doctors’ surgeries, but whose skills are currently underutilised. 

The lack of automation in pharmacy systems and physical constraints within premises prevent them realising their full diagnostic potential. 

But things are changing. Similar to the evolution of personal computers in recent decades, MedTech is now adapting to this demand. 

The commercialisation of the testing devices is primarily being driven by American computer hardware companies rather than traditional players in the MedTech sector, with growing competition from China and India which are developing an ever more prominent role in the industry, driven by the vast markets and a growing middle-class interest in healthcare. 

…..

Ivor Campbell is chief executive of UK-based Snedden Campbell, a specialist recruitment consultant for the global medical technology industry. 

More here:

https://www.medicalrepublic.com.au/to-boldly-diagnose-day-of-the-tricorder-is-at-hand/104882

It is impressive just how much progress appears to be happening in the technologies we would need for a tricorder!

Clearly there is a shrinking job needed to create a hand-held device but I suspect that in time we will see that issue solved.

Stand by for some exciting announcements in the next few years!

David.

Tell Us Something That We Did Not Already Know! Time To Start Again.....

This appeared last week:

07 February 2024

My Health Record ‘not useful’: Cancer Council

Government Public Health

By Harriet Grayson

The platform is not providing useful data on cancer incidence and services, an inquiry has heard.

My Health Record is not being used for its intended purpose by most health providers in Australia, according to Cancer Council Australia.  

Speaking to a Senate Committee investigating equity barriers for rare cancer patients, Megan Varlow, CCA’s director of cancer control policy, told members that My Health Record was not functioning as a platform for national data collection for cancer organisations, particularly given its lack of appropriate application across the health system.  

“My Health Record isn’t the place that we get data for people who are living and affected by cancer,” she said. 

“Most organisations, clinicians, hospitals, services are not using My Health Record in the way that it’s designed, so it’s not useful.  

“We would be very supportive of increased uptake and use of My Health Record. Right across the system, from primary care through hospitals, aged care, community settings, the use of MHR in the way that it was intended will make a big difference. 

“Seeing that play out in real life is continuing to be a challenge.” 

While cancer organisations benefited from a wealth of data from various data collections, Ms Varlow said a national data framework was vital for streamlining and standardising these collections. 

“We are lucky in that cancer is a notifiable disease in Australia,” she said. 

“The cancer registries in states and territories and the clinical cancer registries that are operated by different organisations and the clinical information that lives within the different clinical trials sets, and the different electronic medical health records across the country, [are] where the data has come from. 

“The idea of a national data framework that really brings all of the different data collections together and implements a national minimum dataset across the country, bringing in genomic and other collections [gathered] at an individual level – that really is what we want to see. 

“That’s one of the actions of the Australian cancer plan, to really see that pulled through.” 

Associate Professor Christopher Steer, medical oncologist at Albury Wodonga Regional Cancer Centre, echoed Ms Varlow’s statements, saying that My Health Record was “not the solution” for improving data collection for rare and less common cancers. 

“My Health Record uptake has been patchy, certainly in the specialists sector,” he  said. 

“It may form part of the solution of what is a complex problem, [but] it is not the solution.” 

As president of Private Cancer Physicians of Australia, Associate Professor Steer said that the organisation would not formally comment on the utility of My Health Record. 

 However, as a private medical oncologist practising in a regional centre, he said he did not think the platform was fit for purpose for standardising cancer data collection across Australia. 

More here:

https://www.medicalrepublic.com.au/my-health-record-not-useful-cancer-council/104901

It really is a pity that the Government will not accept that the myHR is as useful as ‘tits on a bull’ and go back to the clinical community to get help in designing a shared system that would be valuable and useful in supporting clinical practice while facilitating improved clinical data sharing and the full range of possible uses to which digital clinical information can now be used.

It is not beyond the wit of man to design and implement a true national system that should  and could deliver real benefits - but the design and scope of this system will need to be user / clinician driven.

I wonder how long we are going to wait for the leadership  needed to throw out what is done now and move on to design and implement something that will be both useful and used?

Will I see it in my fast running out lifetime? I am not sure at all!

David.

AusHealthIT Poll Number 733 – Results – 11 February, 2024.

Here are the results of the poll.

Do You Believe Introduction Of The myHealthRecord Has Made A Significant Positive Impact On The Quality And Safety Of Clinical Health Services In Australia?

Yes                                                                          1 (4%)

No                                                                          27 (96%)

I Have No Idea                                                        0 (0%)

Total No. Of Votes: 28

As clearer outcome as you can get. The bottom line is that  the myHealthRecord is a fizzer!

Any insights on the poll are welcome, as a comment, as usual!

A great number of votes. But also a very clear outcome! 

0 of 28 who answered the poll admitted to not being sure about the answer to the question!

Again, many, many thanks to all those who voted! 

David.

One Man’s View On What We Can Do To Control AI

This appeared last week:

How we can control AI

By Eric Schmidt

The Wall Street Journal

12:26PM January 31, 2024

Today’s large language models, the computer programs that form the basis of artificial intelligence, are impressive human achievements.

Behind their remarkable language capabilities and impressive breadth of knowledge lie extensive swathes of data, capital and time.

Many take more than $US100m ($152m) to develop and require months of testing and refinement by humans and machines. They are refined, up to millions of times, by iterative processes that evaluate how close the systems come to the “correct answer” to questions and improve the model with each attempt.

What’s still difficult is to encode human values. That currently requires an extra step known as Reinforcement Learning from Human Feedback, in which programmers use their own responses to train the model to be helpful and accurate. Meanwhile, so-called “red teams” provoke the program in order to uncover any possible harmful outputs. This combination of human adjustments and guardrails is designed to ensure alignment of AI with human values and overall safety. So far, this seems to have worked reasonably well.

But as models become more sophisticated, this approach may prove insufficient. Some models are beginning to exhibit polymathic behaviour: They appear to know more than just what is in their training data and can link concepts across fields, languages, and geographies. At some point they will be able to, for example, suggest recipes for novel cyberattacks or biological attacks — all based on publicly available knowledge.

There’s little consensus around how we can rein in these risks. The press has reported a variety of explanations for the tensions at OpenAI in November, including that behind the then-board’s decision to fire chief executive Sam Altman was a conflict between commercial incentives and the safety concerns core to the board’s non-profit mission.

Potential commercial offerings like the ability to fine-tune the company’s ChatGPT program for different customers and applications could be very profitable, but such customisation could also undermine some of OpenAI’s basic safeguards in ChatGPT.

Tensions like that around AI risk will only become more prominent as models get smarter and more capable.

We need to adopt new approaches to AI safety that track the complexity and innovation speed of the core models themselves.

While most agree that today’s programs are generally safe for use and distribution, can our current safety tests keep up with the rapid pace of AI advancement? At present, the industry has a good handle on the obvious queries to test for, including personal harms and examples of prejudice. It’s also relatively straightforward to test for whether a model contains dangerous knowledge in its current state.

What’s much harder to test for is what’s known as “capability overhang” — meaning not just the model’s current knowledge, but the derived knowledge it could potentially generate on its own.

Red teams have so far shown some promise in predicting models’ capabilities, but upcoming technologies could break our current approach to safety in AI. For one, “recursive self-improvement” is a feature that allows AI systems to collect data and get feedback on their own and incorporate it to update their own parameters, thus enabling the models to train themselves. This could result in, say, an AI that can build complex system applications (e.g., a simple search engine or a new game) from scratch.

But, the full scope of the potential new capabilities that could be enabled by recursive self-improvement is not known.

Another example would be “multi-agent systems,” where multiple independent AI systems are able to co-ordinate with each other to build something new.

Having just two AI models from different companies collaborating together will be a milestone we’ll need to watch out for. This so-called “combinatorial innovation,” where systems are merged to build something new, will be a threat simply because the number of combinations will quickly exceed the capacity of human oversight.

Short of pulling the plug on the computers doing this work, it will likely be very difficult to monitor such technologies once these breakthroughs occur. Current regulatory approaches are based on individual model size and training effort, and are based on passing increasingly rigorous tests, but these techniques will break down as the systems become orders of magnitude more powerful and potentially elusive. AI regulatory approaches will need to evolve to identify and govern the new emergent capabilities and the scaling of those capabilities.

Europe has so far attempted the most ambitious regulatory regime with its AI Act, imposing transparency requirements and varying degrees of regulation based on models’ risk levels. It even accounts for general-purpose models like ChatGPT, which have a wide range of possible applications and could be used in unpredictable ways. But the AI Act has already fallen behind the frontier of innovation, as open-source AI models — which are largely exempt from the legislation — expand in scope and number.

President Biden’s recent executive order on AI took a broader and more flexible approach, giving direction and guidance to government agencies and outlining regulatory goals, though without the full power of the law that the AI Act has. For example, the order gives the National Institute of Standards and Technology basic responsibility to define safety standards and evaluation protocols for AI systems, but does not require that AI systems in the US “pass the test.” Further, both Biden’s order and Europe’s AI Act lack intrinsic mechanisms to rapidly adapt to an AI landscape that will continue to change quickly and often.

I recently attended a gathering in Palo Alto organised by the Rand Corp. and the Carnegie Endowment for International Peace, where key technical leaders in AI converged on an idea: The best way to solve these problems is to create a new set of testing companies that will be incentivised to out-innovate each other — in short, a robust economy of testing.

…..

Eric Schmidt is the former CEO and executive chairman of Google and cofounder of the philanthropy Schmidt Sciences, which funds science and technology research.

The Wall Street Journal

The full article is here with suggestions on how to check if the Ais are getting ahead of themselves and US!:

https://www.theaustralian.com.au/business/the-wall-street-journal/how-we-can-control-ai/news-story/454fae637233dada7d0adf7b6ff99541

Worth a read to get a handle on the issues surrounding all this!

David.

This Looks Like (And Indeed Is) A Must Not Miss Paper On AI In Health.

This appeared last week:

Collective action for responsible AI in health

19 Jan 2024

Brian Anderson, Eric Sutherland

Publisher

OECD Publishing

Health services planning Health Primary health care Person centred Artificial Intelligence (AI)

Resources

Collective action for responsible AI in health

Description

Artificial intelligence (AI) will have profound impacts across health systems, transforming health care, public health, and research. Responsible AI can accelerate efforts toward health systems being more resilient, sustainable, equitable, and person-centred. This paper provides an overview of the background and current state of artificial intelligence in health, perspectives on opportunities, risks, and barriers to success. The paper proposes several areas to be explored for policy-makers to advance the future of responsible AI in health that is adaptable to change, respects individuals, champions equity, and achieves better health outcomes for all.

The areas to be explored relate to trust, capacity building, evaluation, and collaboration. This recognises that the primary forces that are needed to unlock the value from artificial intelligence are people-based and not technical. The OECD is ready to support efforts for co-operative learning and collective action to advance the use of responsible AI in health.

Publication Details

DOI: 10.1787/f2050177-en

Copyright: OECD 2024

License type: All Rights Reserved

Access Rights Type: open

Series: OECD Artificial Intelligence Paper 10

Post date: 30 Jan 2024

----

Here is the link:

https://apo.org.au/node/325384

All I can say is that time spent reading this will provide a very useful perspective on what is happening globally and where to look next to follow up advances in this area.

Download the .pdf and I think you will be very pleased with what you read in the 41 pages linked below the referring page. It is very up-to-date and well referenced with material from 2023.

Enjoy and be grateful for the work that has already been done! I am.

David.

We Seem To Be Under Attack From AI From All Sides.

This appeared last week:

Special AI laws needed for financial services: Longo

Tom Burton and James Eyers

Jan 31, 2024 – 6.07pm

ASIC chairman Joe Longo says he is concerned about the high risks associated with AI and financial services, and he is unconvinced current rules will be enough to prevent unfair practices.

Risks from data poisoning, model manipulation and generative AI making up answers (so-called hallucinations) were warnings for firms not to become over-reliant on AI models that can’t be understood, examined or explained, Mr Longo warned.

To promote innovation, the federal government has embraced a light-touch voluntary approach to AI oversight, but with special rules to be developed for higher-risk environments such as healthcare and financial services.

Mr Longo endorsed the recent federal AI review’s finding that existing laws do not adequately prevent AI-facilitated harms before they occur.

“It’s clear … that a divide exists between our current regulatory environment and the ideal,” he told an AI governance conference at University of Technology Sydney’s Human Technology Institute on Wednesday.

“There’s a need for transparency and oversight to prevent unfair practices – accidental or intended. But can our current regulatory framework ensure that happens? I’m not so sure,” Mr Longo said.

“Does it prevent blind reliance on AI risk models without human oversight that can lead to underestimating risks? Does it prevent failure to consider emerging risks that the models may not have encountered during training?”

The ASIC chairman said current laws meant there were already obligations for boards of companies using AI applications and that firms should not make the mistake of thinking it was the Wild West as far as AI goes.

“Businesses, boards, and directors shouldn’t allow the international discussion around AI regulation to let them think AI isn’t already regulated. Because it is,” he said. He promised ASIC would continue to act, “and act early” to deter bad behaviour.

But Mr Longo pointed to AI-driven credit checks that arbitrarily blocked customers from getting loans as examples of current rules struggling to be effective and the need for special regulations to stop financial harm.

“Will they [customers] even know that AI was being used? And if they do, who’s to blame? Is it the developers? The company?

“And how would the company even go about determining whether the decision was made because of algorithmic bias, as opposed to a calculus based on broader data sets than human modelling?”

He said AI fraud controls raised similar risks.

“What happens to the debanked customer when an algorithm says so? What happens when they’re denied a mortgage because an algorithm decides they should be? When that person ends up paying a higher insurance premium, will they know why or even that they’re paying a higher premium? Will the provider?”

“...with ‘opaque’ AI systems, the mechanisms by which that discrimination occurs could be difficult to detect.”

“Even if the current laws are sufficient to punish bad actions, their ability to prevent the harm might not be,” Mr Longo said.

The market regulator also raised concerns about AI-powered investment apps.

“When, as a system, it learns to manipulate the market by hitting stop losses, causing market drops and volatility… when there’s a lack of detection systems… yes, our regulations around responsible outsourcing may apply – but have they prevented the harm?

“Or a provider might use the AI system to carry out some other agenda, like seeking to only support related party product, or share offerings in giving some preference based on historic data,” he said.

It was important for policymakers to ask the right questions about AI, Mr Longo said.

“And one question we should be asking ourselves again and again is this: ‘Is this enough?’”

Questions about transparency, explainability and the rapidity of the technology deserved careful attention.

“They can’t be answered quickly or off-hand,” he said. “But they must be addressed if we’re to ensure the advancement of AI means an advancement for all.

APRA, he said, recognised AI’s ability to “significantly improve efficiency” in the system and to improve innovation which was good for customers, but did involve a variety of risks that lenders had to be attuned to.

Mr Lonsdale said it was important for banks to have the right controls for AI apps.

“So all of that is wrapped up in now, in CPS 230 [the new standard on operational risk], which is coming into play, and so, at this point in time, we think we’ve got enough in terms of the regulation to guide through the risks that we’re seeing.”

More here:

https://www.afr.com/politics/federal/special-ai-laws-needed-for-financial-services-longo-20240131-p5f1b4

I found this a fascinating article as it raised so many potential issues and problems I could barely keep up.

I am not sure we can rely on the regulators to catch all potential problems do it will be up to us all to remain ‘alert but not alarmed’!

I hope we can avoid too much in the way of unanticipated fraud!

David.

You Can Be sure This Is Just The Beginning Of What Will Be Possible In Years To Come.

 This appeared a few days ago:

Gene therapy hailed as ‘medical magic wand’ for hereditary swelling disorder

Single-dose treatment transformed lives of patients with potentially deadly condition in first human trial

Medical research

Ian Sample Science editor @iansample

Thu 1 Feb 2024 09.00 AEDT

A groundbreaking gene therapy has been hailed as a “medical magic wand” after the treatment transformed the lives of patients with a hereditary disorder that causes painful and potentially fatal swelling.

Patients who took part in the first human trial of the therapy experienced a dramatic improvement in their symptoms, and many were able to come off long-term medication and return to life as normal.

Dr Hilary Longhurst, the principal investigator at Te Toka Tumai, Auckland City hospital, said the single-dose therapy appeared to provide a permanent cure for her patients’ “very disabling symptoms”.

Hereditary angioedema, or HAE, is a rare disease that affects about one in 50,000 people. It is caused by a genetic mutation that leaves patients with leaky blood vessels. This produces erratic bouts of swelling that typically affect the lips, mouth, throat, bowels, hands and feet.

Attacks strike as often as twice a week and last from hours to days. People can end up bedridden if the swelling affects the bowel, and its disfiguring effect on the face can stop people leaving the home. The most serious flare-ups affect the throat and can lead to suffocation and death.

Cleveland, a 54-year-old from Suffolk who took part in the trial, has been free from attacks since having the therapy 18 months ago. “I’ve had a radical improvement in my physical and mental wellbeing,” he said. “The randomness, unpredictability and potential severity of the attacks has made trying to live my life almost impossible. I spent my life constantly wondering if my next attack would be severe.

“The swellings are painful and disfiguring. I was embarrassed to go out in case of an attack. I’ve been hospitalised with swellings on my neck and throat that have affected my ability to breathe.”

Judy Knox, a nurse in New Zealand who also took part in the trial, said the therapy was “like a medical magic wand”. Before her diagnosis, she suffered abdominal swelling with vomiting and severe pain that lasted for days. Dental work prompted dangerous swelling in her mouth, which threatened to suffocate her. “It’s changed my life,” she said.

Knox previously managed the condition with androgen medication, but supplies have not always been reliable. She is now off the medication and feels she has a “whole new life”.

HAE is caused by a mutation in the C1 inhibitor gene. When the gene stops working, people overproduce a protein called kallikrein. This drives the buildup of another protein, bradykinin, which is responsible for the leaky blood vessels and swelling.

Ten patients took part in the small phase-one trial in the UK, New Zealand and the Netherlands. Each received an infusion of “nanolipids” designed using Crispr, a Nobel prize-winning gene editing tool, to enter liver cells and knock out the kallikrein gene. The therapy stops the body overproducing bradykinin, with dramatic effects for the patients.

“It’s transforming patients’ lives,” said Dr Padmalal Gurugama, a consultant in clinical immunology and allergy at Cambridge University hospital. “My patient was having attacks every three weeks and that gentleman has not had any attacks in the past 18 months. He is not taking any medications. That is amazing.”

The results from the first patients are published in the New England Journal of Medicine, and larger trials are under way. Doctors have treated 25 more patients in a phase-two trial and hope to recruit for a final phase-three trial next year.

Despite the dramatic results, the therapy is not expected to be available soon. Beyond proving itself in remaining trials, such one-shot gene therapies are among the most expensive treatments in the world, and far from a shoo-in for the NHS.

More here:

https://www.theguardian.com/science/2024/jan/31/gene-therapy-hailed-as-medical-magic-wand-for-hereditary-swelling-disorder

This is really very good news! There are many diseases that are caused by a single genetic mistake that could be remedied if there was a clever way of disseminating a change throughout the body.

This has been achieved in this disease – and the approach may work for some other diseases – but actually repairing the genome in live patients will require a set of techniques we are still working on. A good first step here but I would not expect rapid progress with many other diseases all that soon!

We just have to wait – but with more hope than before!

David.