What’s the evidence for vaccines?

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BBC Sounds, Music, Radio, Podcasts.

This is the podcast of BBC Inside Science first broadcast on the 7th of August 2025.

Hello, US Health Secretary Kennedy pulls half a billion dollars in mRNA vaccine research.

Why?

And what will the fallout be for scientists and society?

Also, we meet the most powerful computer in the UK to see what it's up to.

Plus, we asked, you really delivered.

Stay tuned for a Tom Leara-inspired Elements Fest.

And broadcaster Caroline Steele joins me in the studio to talk through the most distractingly sexy breaking science stories of the week.

Caroline, what are you talking about?

So I've got astronomers using satellites to chase a mystery object, what really killed Napoleon's army, and divorcing birds.

Okay, looking forward to that, but let's start with the money.

Half a billion dollars of it.

That's how much the US Department of Health and Human Services declared this week that they were cancelling from mRNA vaccine development.

You probably best know mRNA from the Pfizer COVID-19 vaccine.

It's a new technology and it won the Nobel Prize in 2023.

In short, mRNA delivers genetic instructions into your cells cells and then your body does the work of producing a harmless copy of the pathogen and the antibodies to fight it.

Health Secretary Robert F.

Kennedy Jr.

is a long-time vaccine sceptic, but he says the reason for pulling the funding is based on claims that mRNA technology poses more risks than benefits for viruses like COVID and bird flu.

But before coming to office, he's repeated a number of widely debunked claims about vaccines.

For example, claims that vaccines cause autism.

We've got the latest press release in front of us, and joining us to scrutinise it is Professor Anne Willis, Director of the MRC Toxicology Unit at the University of Cambridge.

Anne, welcome to Inside Science.

Nice to talk to you.

First off, can I read you this?

The data shows these vaccines fail to protect effectively against upper respiratory infections like COVID and flu.

Let's fact check that.

Is that true and what data might they be referring to?

That's not true.

The COVID RNA vaccines were highly effective against severe infection and they were moderately effective against systematic disease and they saved millions of lives.

Okay, so what data might they be talking about?

Is there any data to the contrary?

No, none at all.

They're very effective vaccines.

It's hard to know where they're coming from on that one.

Okay, then we've got this.

We're shifting that funding towards safer, broader vaccine platforms that remain effective even as viruses mutate.

Is that him saying vaccines aren't safe or that they can't cope with mutating viruses?

What's the research say to that, Anne?

I think it's mixing up several things at once here and coming up with something that's not quite correct.

Some of the other older vaccines, for example against measles, are very efficacious for a very long period of time.

You don't need to change those sorts of vaccines.

But things like flu and COVID, the viruses themselves rapidly mutate.

So you're always going to have to update and change those vaccines as they move forward.

There are older vaccine platforms out there that would work, but it doesn't mean the RNA ones don't work.

They are safe and they are effective.

So that's not true at all.

Can I just check vaccine platforms?

What's that mean here?

Oh, I mean, things like the CHADOX vaccine, which is a viral-based vaccine.

Other platforms can include using an inactivated version of a virus.

So, vaccine platforms just mean different types of vaccine.

Yeah, different types of the whole range of different types of vaccine technologies out there.

The real plus for the RNA vaccines are that you can make vaccines really, really quickly.

So, you could go from a virus to a vaccine in probably six to eight weeks.

And the standard vaccine might take up to six months to make.

And the other thing is they're very cheap to make as well.

So, quicker and cheaper are two things in favour of mRNA vaccines.

But to go back to this press release again, it goes on to say technologies that were funded during the emergency phase but fail to meet current scientific standards will be phased out in favour of evidence-based, ethically grounded solutions like whole virus vaccines and novel platforms.

First off, what's a whole virus vaccine mean?

You purify the virus itself and then you inactivate it often by heating activation.

So you would be vaccinating somebody with an inactive version of the whole virus.

And that can be effective.

The one that they made for COVID wasn't hugely effective because often when you heat viruses up to inactivate them, you can end up changing the proteins on the surface.

So, you don't always get a brilliant response to a whole virus.

That's another way of doing it.

But again, that's a slow type of thing to do.

Okay.

And also, Anne, within that statement is the suggestion that

mRNA vaccines were good enough during a pandemic, but actually, now that that we're no longer in a pandemic, we don't need to use things like that that fail to meet current scientific standards.

Is that true?

No, not at all.

I don't know what they're referring to here.

The work's been very carefully done.

The scientific standards were as high for any other vaccine.

It was all passed by the MHRA, FDA, for example.

Things were fully, properly scrutinised before they went into people.

There was nobody cut any corners here.

This is all done properly with the same standards applied to the RNA vaccines vaccines as it's applied to any medicine product that goes into humans.

That's simply not true.

Okay.

Well thank you for the fact checking.

I mean it is a bit baffling then that this is the way that the Department of Health is going to go.

Can we talk about the implications if half a billion is withdrawn from this area of research?

In the UK and I guess in Europe we are more enlightened on the RNA vaccines compared to what's going on in the US at the moment.

These new advanced therapeutics, they call them, of which the RNA vaccine technology is one, is a priority area with funding in this space within the UK.

But it's a real disaster for my colleagues in the US.

This work will just stop.

And also, if they were concerned about the safety, I'm not sure what they're referring to when they say this,

surely the best way to actually improve things is to do more research, not cut it all together.

This technology is transformative, not only for making vaccines, but also for the cancer vaccines that are coming through.

They're all RNA-based and they are phenomenal and will save lives.

And the technology, the same technology for the RNA vaccines, can also be used to make protein replacement products that can be used to treat rare diseases.

If you stop the development of one aim, one part of the technology, it'll have broader implications as well as just on the vaccine work.

How will that affect people who would otherwise get these vaccines?

It's a bit hard to know.

I mean, the real risk is that there's another pandemic comes through and America won't be prepared.

This must be really frustrating for you, no?

Yes, I mean it is, it is frustrating and profoundly disappointing because it's not based on scientific fact.

It's based on a number of loosely thought-through ideas that have been pulled together to kind of and basic misunderstanding and misinformation, particularly around the safety.

Okay, well thank you Professor Anne Willis for joining us.

I think you've been incredibly clear on what the science actually is.

Thank you.

It's very nice to talk to you today.

And if listeners want to to hear more about the US cuts to science, can I recommend the documentary White Coats vs.

the White House with Roland Pease?

It's on Sunday lunchtime on Radio 4.

Staying with the big money projects, the UK's most powerful supercomputer is now up and running.

It's hoped that the £225 million computer developed at the University of Bristol will be able to use AI to develop new drugs and vaccines, among many other things.

Inside Science thought we'd like a closer look.

So here's reporter Dan Welsh.

It's a quiet day here on the outskirts of Bristol and there's little to give away that in the big glass-fronted building next to me is the most powerful computer the UK has ever seen.

Isambard AI is of course named after one of Bristol's most famous sons, the 19th century engineer Isambard Kingdom Brunel.

His Clifton suspension bridge high above the River Avon has become one of the city's most iconic symbols.

Now, both the team here from the University of Bristol and the UK government are hoping this new supercomputer will help bridge the gap in the global AI race.

Well, I'm joined here by Professor Simon McIntosh Smith, Director of the Bristol Centre for Supercomputing.

Hello, Simon.

Hello.

Now, we are just outside the room that houses Isambard AI.

We're in a big black cage, but then inside that cage, there is another structure.

Can we go in and have a look?

I'd love to take you inside to see it.

Okay, so here we are.

It's a lot cooler in here than it is outside.

It's much cooler.

We have to keep the air temperature really quite ambient so that the system doesn't overheat.

When we talk about technology progressing, a lot of the time we seem to almost measure that progression in terms of it getting physically smaller.

You look at the massive early computing devices shrinking down until they could fit under our desks at home and then becoming laptops we could fit in our bags and then smartphones we carry in our pockets.

That isn't the case here though, this is huge.

It is still pretty big but actually in some ways they have still really shrunk down.

The miniaturization has continued.

So what we're looking at in this room is about 12 meters by 12 meters of hardware equipment.

In the past this would have been something sort of football field size.

So they really have shrunk down.

So we've walked in here and we can see there are various banks and there's a big wall of what look like lots of different almost plug-in devices and there's various red and blue wires coming out of them and linking them all together.

This isn't your typical computer, is it?

It really isn't.

The whole thing is constructed of many, many processors all in parallel.

And Isambard AI is optimized for artificial intelligence.

And so for that we use the very latest AI optimized processors from a company called Nvidia.

We connect them all together with a super fast network.

The network is 200 gigabits, which is something like 2,000 times faster than the network you'll have at home.

And we connect nearly 5,500 of these NVIDIA chips all together to make this one big supercomputer.

So, this is the most powerful computing device the UK has ever seen.

And along with another supercomputer called Dawn at the University of Cambridge, a smaller supercomputer that you're going to be working with, it's increasing the UK's computing capacity to 23 AI exaflops.

What on earth does that mean?

It's a huge measure of performance.

It's almost like our sort of miles per hour rating.

But what's it really mean?

To put it into context, if we had everyone in the world do one little calculation every second, so maybe you add two numbers together or multiply two numbers together.

If everyone on earth did that every second, 24 hours a day, 365 days a year, it would take everyone on Earth 80 years to do what Isenbard AI can do in just one second.

So what does this amount of computing power allow you to do that couldn't be done before?

I imagine you're not going to be using this to play Minesweeper.

I certainly hope not.

But the kinds of things that are possible, the first one that people kind of hear of today is things like training large language models.

So many listeners may have played with things like ChatGPT.

We actually didn't have the ability to train something like ChatGPT in the UK.

But now with Isambard we do.

And actually even the latest large language models, the biggest ones coming out of the the big companies, we can now train those from scratch in the UK.

So we can create UK versions of these things where we know exactly what data went into them, you know exactly how they were run.

So that's called a sovereign AI capabilities.

That's one of the big things that's now going to be possible with this level of compute power.

Well we can also speak to a couple of the scientists who are starting to use Isambard AI to help power some very innovative research.

We're joined by Dr.

James Pope, senior lecturer in the School of Engineering, Mathematics and Technology at the University of Bristol.

Hi James.

Hi.

You are investigating how to better detect cancerous moles in different skin tones.

Yes, that's correct.

AI models may be able, and people are using them, to detect whether it might be cancerous or benign.

And what we were interested in was might there be tone bias?

In other words, might it work better for lighter tones than darker tones?

And we were interested in answering that question.

We sort of hear about these perhaps unintentional but of course really serious biases in medicine, perhaps because of clinical trials not having been run on a widely representative range of people.

Really significant problem.

So how are you using this supercomputer to try and help resolve that in this case?

So what we did is we, there were existing data sets out there and we thought that, well, maybe there might be a bias because as you suggested, there were many more clinical trials of data with lighter skin for skin cancer than darker.

So we corrected for that.

We actually addressed that.

And really what we needed was a good AI model that would be able to classify cancer and benign.

And to do that,

it took a lot of computing power and we needed that.

And that's actually what Easonbard did for us.

Where are you at in that process at the moment?

So we used got access to Easonbard and were able to show that there was bias with three data sets from a commonly used data set, that there was actual bias.

In other words, it did do better for detecting cancer in lighter skin tones than darker skin tones.

And the next step will then be to see exactly what that is.

So we know it's not the data balance.

We addressed that.

So now we want to understand using explainable AI techniques to understand where that bias comes from and then think about how we might mitigate that.

So those are the next steps.

And could you have done this in the past without this kind of computing power?

No.

So

as an example or a little bit of an idea for training the model on one set of hyperparameters took about five hours on one of our high-end servers at the university, we needed to do this like 10,000 times.

So it's just not something we feasibly could have done without Isambard.

Well, thank you, Dr.

James Pope.

I'm also now going to head to speak to someone who's been using Isambard to analyze how we carry out everyday tasks around the house.

I am Professor Dima Dahman at the University of Bristol in the Department of Computer Science.

So Dima, tell me, what have you been using Isambard for?

We started using the pilot version of Isambard AI to analyze footage from wearable cameras.

So these are footage of people just putting a head-mounted or a glass mounted camera and going around doing their daily lives.

And our objective is to understand what they do, why they're doing it and what do they plan to do next.

What is it that you're looking for in that and what do you hope it's going to be used for?

There are two things we're trying to do.

One, to basically interpret this and assist the human, the person wearing the camera, but there is also a huge potential for this to do imitation learning for robotics.

If we're able to understand how a human naturally performs a task, will we get robots to do that?

Many people say robots are very far behind.

They're very, you know, because we're feeding them instructions of how to do things.

And people wonder whether if they just learn by observing, whether that will give them the agility, the naturalness that humans can perform tasks in.

And we can only do that by observing and analyzing footage of humans just doing what they do naturally successfully.

Well, let's have a quick look at some of the footage that you've gathered from people filming themselves all around the world.

This is a recording in Italy, and we can see just people going around opening cupboards, unzipping bags.

This is somebody in their kitchen in Italy.

Yes, this is someone in their kitchen in Italy.

They look like they're unpacking their lunch bag or something, and they're discarding some of their cutlery.

We're moving here to footage actually from the UK, and we see people slicing through an onion.

Now you've got all of this video footage.

Why do you need to use this new supercomputer, Isambard, to analyze this?

You couldn't do that before.

Despite the fact that we collected this amazing resource of 3,600 hours from these 900 people, we never were able in the UK to put all this resource together into one project.

But thankfully because of Isambard and because of this investment, we will for the first time, three years years down the line, be able to do some of our ambition, put all this footage and be able to understand goals and intentions, and be able to predict what people could do next.

This is in particular very important as we think about the potential of these devices to be able to give warnings, to give advice, all the way from reminding someone who might have dementia about how they did a particular action before, to warning a factory worker about the risk that they're doing, like something they shouldn't be touching.

So there is plenty of potential if we are able to anticipate what people should do next from footage.

And that's our project.

Well, I'm back with Professor Simon McIntosh Smith.

And Simon, we've been hearing about just a couple of the pieces of research this supercomputer is being used for.

Now it's fully powered up.

This site has been funded by the UK government.

It costs a lot of money.

Why is this so important to the UK government and where it places the UK in terms of the global supercomputing world?

I think artificial intelligence is expected to be one of the next big disruptions,

almost as big as the internet, could be as big as steam power even.

And if that's true, we really need to be at the forefront of this revolution.

You wouldn't want to be left behind when the internet was coming out or when steam engines were being developed.

So if it really is that big, we need to make sure the UK is at the forefront of all of that and we need the computing power to enable that.

That's really where Is and Bard AI kicks in.

Simon McIntosh Smith there, director for the Bristol Centre for Supercomputing at the University of Bristol.

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Caroline Steele is with me in the studio.

Caroline, before we get stuck into this week's new discoveries, I've got something to play you.

Something of a treat.

So, satirist and mathematician Tom Lehrer died last week.

Now he's best known for his Elements song which lists all of the elements in the periodic table.

However, it was first recorded in 1959 and guess what?

Science has moved on.

So last week we challenged our Inside Science listeners to update his Elements song for, in the words of Ian from Hayton, All the new elements now on the shelf, named after countries or after yourself.

Excellent.

So new elements, new songs please.

Pleasingly, but also unfortunately, you've sent us more recordings than we have time to play.

But let's hear a few of our favourites.

Here's Alan from North Allerton.

There's Dodnium and Borium and Hassium Nihonium, Cyborgium, Magnirium, and also rhodopodium, and tennessine fluorovium, as well as copernicium, lorentium lascovium, and tasty livermorium.

Thank you, Alan.

I feel like we might have a new inside science theme tune there.

I think we might do we have to pay royalties.

I don't know.

Moving swiftly on from that terrible thought, um, we've got a very poetic submission from Diana in Farringdon.

Moscovium organison, the US helped with tennis scene.

The fourth is from Japan, Nihoni, Yamland of the Rising Sun.

Each of these four new elements contracts to letters here we go.

NHMCTSOG.

I do prefer to sing this slow.

And though my chemistry is silch and not a known reliance, I can sing of elements, they're real.

I must tell inside science.

Wow, that was beautiful.

Yeah, Diana, congratulations.

What a range.

You hit the high notes and the low notes.

William in London sent us this

along with an apology to his school piano teacher.

Hey!

I'm gonna have this tune stuck in my head at least for the rest of the day.

That was incredible, honestly.

What a spread.

What a spread.

I mean we've got one more to play us out but I think the late great great Tom Lero would be proud, though.

Now, from stars in their eyes to comets in our vicinity, right, Caroline?

Yes.

So, Monnie, have you heard of 3 Eye Atlas?

No, I can't say I have.

So it's an interstellar object that's currently hurtling through our solar system, and it's going to swing around the sun and disappear back into the depths of the cosmos within the next few months.

And it's only the third object that we've ever detected that's entered our solar system from outside of of it.

So are we going to let it alone or are we going to interfere with it?

Well, for science.

So astronomers are looking at whether or not we have a chance of landing on or flying near this object to learn more about it.

But Atlas is moving at 60 kilometers per second, so it's not going to be easy.

There are proposals to reroute NASA and ESA missions already in space or to repurpose sort of shelved spacecraft projects and launch them.

But it is a huge ask to suddenly launch a spacecraft or redirect one.

It's not as easy as it looks in the sci-fi movies.

So personally, I'm not holding my breath.

But I did stumble across an interesting project that's coming up.

So ESA is currently working on the Comet Interceptor spacecraft, which is due to be launched in 2029.

And the plan is for it to just loiter, waiting for the discovery of an interstellar object that it can survey.

So it would be perfect for when the fourth interstellar object enters our solar solar system.

And then we can really work out what it is because we genuinely don't know what this object is.

It's probably a comet.

It could be older than our solar system.

So it could be like 7 billion years old.

But it's a bit of a mystery and we're not going to be able to learn that much about it unless we can get closer to it.

Talking of mysteries.

What really killed Napoleon's army?

Okay, so should we start with a little history lesson?

Yeah, sure.

So Napoleon and 600,000 troops invaded Russia in 1812 and it didn't go very well, so they retreated.

But the process of retreating was really, really dangerous.

About half of the soldiers were wiped out by disease, starvation, extreme cold, and historical reports from survivors have sort of suggested that typhus and trench fever were the two main causes of death.

But French scientists have done some really interesting state-of-the-art DNA analysis on the teeth of 13 soldiers which were buried in Lithuania, which was one of the main places where retreating soldiers died.

And they found no evidence of typhus or trench fever.

Oh a mystery.

So what have they found evidence of?

So instead they found the bacteria Sarmonella enterica, which causes paratyphoid fever and you get that by ingesting food or water contaminated with feces of someone else who's infected.

Lovely.

In any extreme scenarios, it can kill you.

They also found Boralia recreintis, which is transmitted by body lice.

It causes relapsing fever.

And it's not often fatal, but in an already weak soldier, it could well have been.

So scientists may have just basically completely turned the historical records on their head.

But these haven't been published in a peer-reviewed journal yet, so the jury is sort of still out.

But it's quite cool that we can even do this.

I think, like DNA analysis could be used to sort of fill in the blanks in historical records, or like in this case, even correct them.

Thank you, Caroline.

and finally divorcing birds.

So this is my favourite one.

A paper's been published in the Proceedings of the Royal Society B and the paper name is great.

It's called Timing and Social Dynamics of Divorce in Wild Great Tits.

So great tits are these small like yellow and black birds.

They're monogamous, they have one partner at a time and from breeding season to breeding season some birds will stay with their partner while others will split and find a new partner.

But what's long been unclear to scientists is how the birds' behaviours in the non-breeding season affect or determine whether or not they stick together or divorce.

But there's this amazing project called the Wythamwood Great Tit Project and it's studied wild bird populations for over 75 years and data from this study shows that early signs of divorce can be seen in the winter, so in between breeding seasons, months before the couples make the choice whether or not to pair up or move on and find a new partner, which again sounds quite human, you know.

With friends, you can sort of tell sometimes months before they break up just by

more bickering.

Well, exactly.

I was going to ask, what are the signs?

Is it, you know, how can you tell if some birds are squabbling?

So they're not that surprising, I would say.

They spend less time together.

They visit feeders at different times and they stop showing a preference for socialising with their breeding partner.

And generally, these effects sort of increase over time, which basically shows that bird divorce, like human divorce, is a socially driven process.

Which, yeah, I think is kind of interesting.

Yeah, a family that eats together stays together as well.

Precisely, that is what the science says.

Well, thank you very much, Caroline.

That's us out of time, unfortunately.

Send your comments and questions to insidescience at bbc.co.uk.

We'll say goodbye from Caroline.

Bye-bye.

Bye from me.

And we're going to play out with one more favourite Tom Lyra update.

This is John in Hereford.

This

periodic table song, it used to list out all of them.

But 60 years later, we find there's many more of them.

Like Hassium, Serbogium, Dubneum Laurencium, Organison, Muscovium, Plano Rather Bodium.

I might have missed a couple, like Neonum and Boreum.

But if I'm being honest, I'm slightly more than bored of them.

You've been listening to BBC Inside Science with me, Marnie Chesterton.

The producers were Jonathan Blackwell, Dan Welsh, and Claire Salisbury.

Technical production was by Sue Mayo and Matt Chamberlain.

The show was made in Cardiff by BBC Wales and West.

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