00:00> > YOU ARE WATCHING BLOOMBERG TECH EUROPE. COMING UP, A.I. DISCOVERY COULD BE THE NEXT FRONTIER OF MEDICINE TO SPEEDING UP DEVELOPMENT. THE TECHNOLOGY PROMISES PLENTY BUT WILL IT DELIVER? WE SPEAK EXCLUSIVELY TO DENNIS HASSABIS THE NOBLE LAUREATE, WHOSE LONDON-BASED ISOMORPHIC LABS HAS THE AMBITION 'TO SOLVE ALL DISEASE.' THE MAN RESPONSIBLE FOR ALL OF ALPHABET’S CORE A.I. WORK AS HEAD OF GOBBLE DEEPMIND IS SETTING THE BAR HIGH FOR ISOMOPHIC. > > THE KIND OF HOLY GRAIL IS TO TACKLE CANCER. BUT WE’VE DONE IT FOR PRACTICAL REASONS AS WELL BECAUSE YOU KNOW, THE CLINICAL ASPECT OF THAT ARE FAVORABLE FOR NEW DRUGS BECAUSE OBVIOUSLY THE DISEASE IS SO SERIOUS WELL, IN THIS EPISODE WE LIFT THE LIDS ON THE A.I. COMPANY WORKING TO TRANSFORM THE WAY WE FIND AND DEVELOP LIFE-SAVING DRUGS IN THE RACE TO REVOLUTIONIZE MEDICINE, ONE COMPANY STANDS OUT FOR ITS WORK TO HARNESS THE POWER OF ARTIFICIAL INTELLIGENCE TO TRANSFORM HOW DRUGS ARE DISCOVERED. ISOMORPHIC LABS WAS CREATED TO COMMERCIALIZE ALPHAFOLD, GOOGLE DEEPMIND'S NOBEL-PRIZE WINNING AI SYSTEM THAT CRACKED THE CHALLENGE OF PREDICTING PROTEIN BEHAVIOR. THEY PARTNERED WITH NOVARTIS FOUNDER & C.E.O. DEMIS HASSABIS, TOLD ME THAT CURING CANCER WOULD BE THE HOLY GRAIL. > > THE MISSION STATEMENT OF ISOMORPHIC LABS IS TO SOLVE ALL DISEASE. WHERE ARE WE IN THAT MISSION? > > WE’RE MAKING A GOOD PROGRESS. WE’RE BUILDING A GENERAL PLATFORM TO HELP TACKLE THE UNDERSTANDING REALLY OF BIOLOGY AND THE CHEMISTRY THAT YOU NEED TO BUY INTO THAT BIOLOGY. I THINK IF IT WORKS OUT, WE SHOULD BE TO TACKLE MANY, MANY DISEASES. > > SO IN TERMS OF DISCOVERING AN A.I. DRUG AND GETTING INTO CLINICAL TRIALS? IS THAT A 2025 PROPOSITION 2026 OR FURTHER OUT? > > WE’RE AT THE PRECLINICAL STAGE. WE JUST HIRED BEN WOLF AND HE’S HEADING UP OUR WORLD CLASS TEAM TO HELP WITH US THE CLINICAL PHASE. BUT WHAT WE’RE FOCUSING ON IS BUILDING THE CORE PLATFORM. AND SORT OF EXTENDING THE WORK WE DID WITH ALPHAFOLD. BUT THERE’S MANY MORE AREAS THAT WE NEED TO GET INTO IN TERMS OF THELY MAKING AN IMPACT ACROSS THE DISCOVER AND WE’RE MAKING GREAT PROGRESS WITH THAT AND THESE FIRST FEW TRIALS ARE EXAMPLES OF WHAT THE PLATFORM MIGHT BE ABLE TO DO. AND THE INTERNAL PIPELINE FOR ISOMORPHIC IS TO US ASKED ON ONCOLOGY AND IMMUNOLOGY. DOES THAT MEAN THAT YOU THINK CANCERS CAN BE SOLVED FIRST AMONG SOME OF THETHAT WE FACE. > > WELL, THAT WAS ALWAYS THE KIND OF HOLY GRAIL TO TACKLE CANCER. BUT WE’VE DONE IT FOR PRACTICAL REASONS AS WELL BECAUSE YOU KNOW, THE CLINICAL ASPECTS OF THAT ARE FAVORABLE FOR NEW DRUGS. BECAUSE OBVIOUSLY THE DISEASE IS SO SERIOUS. AND SO THERE ARE A NUMBER OF REASONS WE PICK THOSE TWO AREAS AND ALSO WHAT WE THINK THE PLATFORM IS GOING TO DO EARLY ON. > > THERE’S THE SPEED AND EFFICIENCY THAT THE PLATFORM BRINGS IT TO. WHEN WE ARE THINKING ABOUT PRECLINICAL A.I. DRUG DISCOVERY -- USUALLY USING THE OLD METHODS. WE'RE TALKING THREE TO SIX YEARS. TO WHAT EXTEND CAN YOU CUT THAT TIME FRAME DOWN? > > IN THE FULLNESS OF TIMES WHEN OUR PLATFORMS MATURE I WOULD LIKE TO SEE THAT CUT DOWN INTO A MATTER OF MONTHS INSTEAD OF YEARS. THAT’S WHAT I THINK IS POSSIBLE. PERHAPS EVEN FASTER THAN THAT. BUT YOU KNOW, WE’LL SEE IF THAT’S POSSIBLE. THERE’S A LOT OF WORK WE’VE GOT TO DO FIRST. BUT YOU KNOW, INITIAL -- OUR INITIAL WORK AND SIGNS ARE PROMISING. > > GETTING TO WORK WHERE WE HAVE THE F.D.A. OR ANOTHER REGULATOR TO GREEN STAMP AND BE SHIPPED OUT TO MARKETS. ARE WE TALKING 6, 7 YEARS A DECADE OR IS THIS EARLY 2030’S? > > RIGHT NOW, WE’RE FOCUSING ON THE DRUG DISCOVERY PHASE. EVEN IF WE IMPROVE THAT BY MONTHS OR WEEKS OR YEARS THERE’S STILL THE CLINICAL & REGULATORY PHASE. AND YOU KNOW, WE’RE GOING TO SORT OF PARTNER ON THOSE THINGS. THAT’S OUR CURRENT PLAN. AT SOME POINT, TO ONCE WE’VE CRACKED THE FIRST STAGE, THINK A.I. CAN ALSO HELP WITH THE CLINICAL STAGE TWO. > > YOU’VE PARTNERED WITH NOVARTIS AND ELI LILLY WHAT DOES THAT TELL US ABOUT WHAT ISOMORPHIC LOOKS IN 5, 10 YEARS DO YOU FOCUS ON PARTNERSHIPS, LICENSING THE TECHNOLOGY OR DO YOU WANT TO BE A FULL STACKED BIOTECH. > > WE’VE HAD GREAT PARTNERSHIPS AND THAT’S HELPING US FIGURE OUT WHAT’S NEEDED FOR THE PLATFORM. THEY’RE WORLD CLASS COLLABORATION. BUT WITH OUR INTERNAL PROGRAMS, YOU KNOW, EVERYBODY IS ON THE TABLE. THOSE ARE GOING WELL TOO. AND WE’LL SEE HOW FAR IT MAKES SENSE FOR US TO CARRY THAT THROUGH. > > DO YOU LOOK TO DEEPEN THOSE RELATIONSHIP BETWEEN NOVARTIS AND ELI LILLY BEYOND WHERE THEY ALREADY ARE? > > YES. WE ANNOUNCED AN EXPANSION FROM THREE TARGETS TO SIX TARGETS. BOTH COLLABORATIONS ARE GOING VERY, VERY WELL. > > > > YOU RAISED BACK IN MARCH $600 MILLION YOU’RE PUTTING THAT INTO PLAY TO BUILD OUT THE PLATFORM. BUT ALSO TALENT SEEMS TO BE PART OF THAT. WHEN YOU THINK ABOUT MARK ZUCKERBERG SIGNING CHECKS FOR $200 MILLION, WHAT DOES THAT SIGNAL TO YOU? > > WELL, THAT’S A SLIGHTLY DIFFERENT MARKET WHICH IS THE PURE A.G.I. MARKET. BUT IT’S AND YOU KNOW, WHETHER OR NOT THAT’S RATIONAL OR NOT, I THINK THE ORGANIZATIONS NEED TO THINK THROUGH THEMSELVES. BUT I DO THINK A.I. WILL BE ONE OF THE BIGGEST TECHNOLOGY THAT HUMANITY WILL EVER INVENT SO IN SOME SENSE THAT IS RATIONAL, BUT ON OTHER HAND SPECIFICALLY WITH ISOMORPHIC WE HAVE SUCH A COMPELLING MISSION OF APPLYING A.I. TO IMPROVE HUMAN HEALTH. WHAT BETTER USE OF A.I. IS THERE THAN THAT? THAT’S A REALLY COMPELLING PROPOSITION FOR OUR INVESTORS AND OUR STAFF > > ALPHA FOLD THREE, YOU SOLVED PROTEIN FOLDING PROBLEM THAT MANY THOUGHT IT WAS UNSOLVABLE. IT GIVES YOU THE ABILITY TO LOOK AT HOW MANY DIFFERENT MOLECULES AND R.N.A. INTERACT WITH PROTEINS. ARE YOU WORKING ON AN ALPHA FOLD FOUR -- OR SOMETHING THAT MOVES THINGS BEYOND THE ALPHA FOLD THREE? WHERE ARE WE IN THAT PROCESS? > > WELL,INTERNALLY, YOU CAN IMAGINE WE HAVE THINGS MUCH MORE ADVANCED THAN ALPHA FOLD THREE WE NEED TO GO BEYOND WHAT ALPHA FOLD CAN DO NOT JUST LOOKING AT THE, YOU KNOW, THE STRUCTURE OF PROTEINS OR THE INTERACTIONS THEY HAVE, BUT ALSO GO INTO CHEMISTRY, YOU KNOW, DESIGNING THE KINDS OF COMPOUNDS THAT ARE GOING TO BIND TO THE PROTEINS AND ALSO THINGS LIKE ACNE PROPERTIES, YOU KNOW, TOXICITY AND MAKING SURE THAT THE PROPERTIES OF THE COMPOUNDS HAVE THE DESIRED PROPERTIES THAT YOU NEED. YOU CAN IMAGINE WE NEED SEVERAL LEVEL BREAK THROUGHS IN ORDER TO REALLY HAVE AN IMPACT > > AND YOU’RE WORKING ON ALL THOSE IN PARALLEL AT PACE -- > > YEAH. > > THAT’S THE MULTI-MODAL APPROACH THAT YOU'RE TAKING AT ISOMORPHIC LABS THAT SOME OF YOUR COMPETITORS AND SOME OTHERS AREN'T. THEY’RE SQUARELY FOCUSED ON ONE THERAPEUTIC OR ONE PARTICULAR TARGET. JUST UNPACK FOR US WHY THAT MAKES SENSE TO GO THE ROUTE THAT YOU'RE GOING THEN. WELL, WE'RE TRYING TO DO IT IN THIS VERY GENERAL WAY, SO WE'RE NOT JUST TRYING SOLVE ONE DISEASE OR FIND ONE THERAPY. ALTHOUGH THAT WOULD BE GREAT. WE’RE TRYING TO BUILD A PLATFORM THAT CAN REVOLUTIONIZE THE WAY THAT WE DO DRUG DISCOVERY. AND POTENTIALLY IN THE FUTURE DISCOVER HUNDREDS OF CURES. AND SO TO DO THAT, WE NEED TO FOCUS ON THE PLATFORM CAPABILITIES MORE THAN ANY SINGLE THERAPY OR SINGLE DISEASE. YOU'VE TALKED RECENTLY ABOUT IF YOU SOLVE INTELLIGENCE, YOU CAN SOLVE ESSENTIALLY EVERYTHING, AND YOU CLEARLY THINK THAT CAN APPLY TO THE WORLD OF MEDICINE. WHAT WOULD BE YOUR NEXT PRIORITY? WHAT WOULD COME AFTER THAT? ONCE YOU TICK THAT HUGE BOX? WELL, I THINK MEDICINE HAS ALWAYS BEEN THE FIRST THING I WANTED TO APPLY A.I. TOO, THAT KIND OF POWERFUL GENERAL A.I. AND WE’RE DOING THAT WITH ISOMORPHIC LABS. BUT I THINK THERE ARE MANY OTHER REALLY IMPORTANT AREAS LIKE ENERGY, HELPING WITH MATERIAL DESIGN. SO, YOU KNOW, I THINK THOSE WOULD BE THE NEXT AREAS THAT HELP WITH CLIMATE AND AND THE ENERGY CRISIS AND ARE LARGE LANGUAGE MODELS, THE PROCESS THROUGH WHICH WE SHOULD LOOK TO ACHIEVE THAT? OR IS THERE SOMETHING ELSE YOU'D BE LOOKING AT? NO, I THINK THE LARGE LANGUAGE MODELS WOULD BE PART OF THE SOLUTION, BUT JUST LIKE WITH ISOMORPHIC, I FEEL LIKE FOR A LOT OF THESE SCIENTIFIC AREAS, YOU ALSO NEED MORE SPECIALIZED MODELS THAT ARE USING THESE GENERAL ALGORITHM IDEAS, BUT THEY’RE ALSO ADAPTED TO THAT PARTICULAR SPECIALIZED SCIENTIFIC AREA. AND I THINK FOR THE NEXT, FIVE, 10 YEARS THAT’S WHAT WE’RE GOING TO SEE. AND THE STRUCTURE IS OFTEN OF ISOMORPHIC LABS RIGHT NOW. DOES THAT MAKE SENSE? THIS CURRENT STRUCTURE IS KIND OF FIVE OR 10 YEARS. HOW DO YOU MANAGE THAT? THAT’S A HUGE AMOUNT TO OVERSEE. YES, IT IS. I DON'T SLEEP MUCH, BUT YOU KNOW, I’M PASSIONATE ABOUT BOTH OF THESE AREAS. AND FOR ME, THAT GIVES ME SORT, YOU KNOW, ENERGY TO DO ALL OF THESE THINGS. AND THERE’S QUITE A LOT OF OVERLAP IN TERMS OF OVERSIGHTS AND THE BREAKTHROUGHS THAT YOU SEE AND EACH OF THE DIFFERENT AREAS THAT CAN HELP EACH OTHER. FOR NOW -- THERE’S A LOT TO SYNERGY BETWEEN THOSE TWO MISSIONS. > > AND IF THE TECHNOLOGY AND SCIENCE PROGRESSES AS YOU HOPE, WHAT WILL IT MEAN FOR YOUR LIFESPAN FOR MY LIFESPAN? > > WELL, LOOK, I THINK THE FIRST STEP -- I THINK IT’S AN EMPIRICAL QUESTION. LET’S FIND CURES TO THESE TERRIBLE DISEASES THAT AND INCREASE HEALTHY LIFESPAN AND WE’LL SEE WHERE WE GO FROM THAT. BUT WE COULD BE AN ENVIRONMENT WHERE YOU AND I HAVE ELONGATED LIFESPANS IF THE TECHNOLOGY COMES TOGETHER POTENTIALLY. I MEAN, OF, COURSE IT'S AN OPEN QUESTION WHAT AGING IS. IS IT A COMBINATION OF ALL THE OTHER DISEASES OR IS IT SOMETHING, YOU KNOW, SPECIFIC ITSELF? AND, YOU KNOW, YOU HAVE DIFFERENT EXPERTS -- I’M NOT AN EXPERT SAYING DIFFERENT THINGS ON THAT FIELD. THE FIRST STAGE WHICH IS UNEQUIVOCALLY GOING TO BE A GOOD THING TO DO PROGRESS, IS TO IS TO CURE THE DISEASES THAT WE, YOU KNOW, AFFECTS US TODAY. > > DENNIS HASSABIS FOUND & C.E.O. OF ISOMORPHIC LABS. HOW SCIENTISTS AT ISOMORPHIC LABS ARE WORKING WITH PHARMACEUTICAL GIANTS TO SOLVE SOME OF MEDICINE'S HARDEST PROBLEMS - WITH AI AT THE CORE. MORE ON THAT RACE TO CHANGE DRUG DISCOVERY FOREVER. WE’RE GOING UNPACK THE DETAILS. THAT IS NEXT. THIS IS BLOOMBERG. > > OK WELCOME BACK. ISOMORPHIC LABS WANT TO DISCOVER AND DEVELOP NEW MEDICINES. I SPOKE WITH MAX, THE COMPANY’S CHIEF A.I. OFFICER. AND REBECCA PAUL HEAD OF MEDICINAL DRUG DESIGN ABOUT THEIR DRUG DESIGN ENGINE AND HOW IT COULD RESHAPE THE FUTURE OF HEALTHCARE. > > WHAT WE’RE DOING AT ISOMORPHIC LABS WE’RE BUILDING THIS DRUG DESIGN ENGINE. SO YOU CAN THINK ABOUT THIS MACHINE WHICH IS ABLE TO COME UP WITH NEW MOLECULE DESIGNS FOR DIFFERENT DISEASE AREAS, DIFFERENT INDICATIONS AND EVEN DIFFERENT MODALITIES., NOT JUST A SINGLE MODALITY. AND, YOU KNOW, UNDERLYING THAT DRUG DESIGN ENGINE ARE A WHOLE SUIT OF AI MODELS. THESE ARE THESE AREE, YOU KNOW, NOT JUST A SINGLE MODEL LIKE ALPHA FOLD. BUT ACTUALLY WE'RE GOING TO NEED, YOU KNOW, MAYBE HALF A DOZEN ALPHA FOLD LIKE BREAKTHROUGHS THAT COME TOGETHER INTO THIS DRUG DESIGN ENGINE. AND MAX, YOU TOUCHED ON ALPHA FOLD. AND MANY IN THE INDUSTRY HAD ASSUME HAD THAT IT WAS ALMOST AN IMPOSSIBLE PROBLEM TO SOLVE WHICH IS THE PROTEIN FOLDING PROBLEM. YOU AND THE TEAM MANAGED TO DO THAT WITH ALPHA FOLD TWO. AND THEN ALPHA FOLD THREE, WHICH GIVES SCIENTISTS AND MEDICAL EXPERTS THE ABILITY TO LOOK AT THOSE MOLECULES INTERACT. YOU TALKED ABOUT THE NEED FOR OTHER MODELS. WHAT COMES BEYOND ALPHA FOLD? WHAT OTHER MODELS DO YOU NEED TO GET THE KIND OF BREAKTHROUGHS THAT YOU AND REBECCA ARE AIMING FOR? > > THERE’S STILL AMOUNT OF ACCURACY TO BE GAINED ON THESE MODELS. WE’RE SEEING BIG STEP CHANGES INTERNALLY WITH OUR NEXT VERSIONS AND ITERATIONS WITH THESE TYPES OF MODELS. AS I TOUCHED ON BEFORE, IT’S NOT JUST ABOUT UNDERSTANDING THE STRUCTURE OF THESE COMPONENTS. THAT’S JUST ONE PART OF THE YOU NEED -- PROBLEMS. YOU NEED TO UNDERSTAND HOW THESE MOLL MOLECULES INTERACT WITH DIFFERENT PARTS OF THE BODY. A COMMON CAUSE OF CLINICAL FAILURE IS FROM TOXICITY. A BIG SOURCE OF TOXICITY IS NOT JUST HOW THEY ACT WITH THE TARGET BUT INTERACTION WITH ALL THE OTHER PROTEINS IN YOUR BODY. AND SOW YOU CAN IMAGINE THAT WE NEED TO UNDERSTAND NOT JUST HOW THESE MOLL MOLECULES INTERACT WITH WHAT WE’RE DESIGNING FOR BUT WITH EVERYTHING ELSE IN THE BODY, THAT’S A BIG TASK. AND THEN, HOW DO WE DESIGN THESE MOLL MOLECULES? BECAUSE MOLECULAR SPACE IS MASSIVE. IT’S SOMETHING LIKE 10 TO THE POWER OF 60. YOU CAN’T ASK THESE MODELS LIKE HOW DOES THIS MOLECULE LOOK? PEOPLE TRIED TO DO THAT. YOU CAN MAYBE FEED, YOU KNOW, 100,000, A MILLION, A BILLION MOLL MOLECULES THROUGH THESE SYSTEMS AND START READING THE ANSWERS. BUT THAT BARELY SCRATCHES THE SURFACE OF THIS MASSIVE MOLECULAR SPACE. THERE’S A HUGE OPPORTUNITY FOR GENRE ACTIVE MODELS, SERVE TO PROCESSES AND AGENTS INSTEAD OF HAVING TO EXHAUSTIVELY SEARCH MOLECULE BY MOLECULE, THEY CAN EFFECTIVELY SEARCH THE ENTIRE SPACE AND TRIAGE IT DOWN. > > YOU TALKED ABOUT THE GENERALIZABLE TECHNOLOGY THAT LABS ARE BUILDING. WHICH IS DIFFERENT THAN SOME OF YOUR COMPETITORS. EXPLAIN WHY THAT IS IMPORTANT AND WHAT THAT’S THE ROUTE YOU’VE TAKEN? > > THAT’S THE KEY FOR WHAT WE’RE BUILDING BECAUSE ULTIMATELY, WE DON’T WANT TO DO JUST A SINGLE DRUG DESIGN PROGRAM. AND THEN WE’RE DONE? NO. WE WANT TO BE BUILDING THIS MACHINE THAT WE CAN APPLY AGAIN AND AGAIN ON ANY TARGET IN ANY DISEASE AREA EVEN AGAINST, YOU KNOW, ANY DIFFERENT MODALITY. SO IT’S REALLY IMPORTANT WHAT DOES GENERALIZED ABILITY MEAN WHEN WE HAVE THESE MODELS THAT ARE TRAINED IN A SET OF DATA. BUT THEN IT COULD BE APPLIED ON SOMETHING COMPLETELY NOVEL. THEY CAN DISCOVER CHEMICAL MATTER THAT’S NEVER BEEN SEEN IN HUMANITY BEFORE. IN PRACTICE WE’RE SEEING THAT BEAR OUT BY A TO DAY. WE HAVE BENCH MARKS THAT MEASURE HOW GENERALIZABLE OUR MODELS ARE. BUT, YOU KNOW, THE PROOF IS IN THE PUDDING. CAN YOU USE THESE MODELS ON DIFFERENTLY DIFFERENT DESIGN COMPANY? > > WITH NOVARTIS AND ELY LILY, CAN YOU GIVE US SOME MILESTONES THAT YOU’VE BEEN ABLE TO ACHIEVE IN THOSE PARTNERSHIPS? > > WE WORK REALLY CLOSELY WITH NOVARTIS. I THINK NOVARTIS INITIALLY CAME OUT AND SAID THESE ARE CHALLENGE TARGETS. WE’VE BEEN WORKING WITH THEM FOR MANY YEARS. AND WE’VE MANAGED TO MAKE REALLY GOOD PROGRESS. SOME OF THEM REPRESENT A PROTEIN MASS WHERE THEY HAVE NOT IDENTIFIED SOME OF THE FIRST CHEMICAL MASSIVE FINDINGS. AND WE’VE MANAGED TO I’D THIGH THOSE. AND THERE ARE SOME INCREDIBLE STEPPING STONES ALREADY. > > WHY DOES IT MAKE SENSE FOR THE INTERNAL PIPELINE TO FOCUS ON IMMUNOLOGY AND ONCOLOGY, SO CANCERS. WHAT WAS THE RATIONALE BEHIND THAT? AND WHAT COULD THE ACHIEVEMENTS BE? > > IT MAKES SENSE. CLINICAL TRIALS ARE MUCH MORE ATTRACTABLE. WE CAN RUN THEM IN A SHORT TIME FRAME. WE ALL KNOW SOMEONE AFFECTED BY CANCER IMMUNOLOGY AFFECT AS HUGE PORTION OF THE WORLD BECAUSE WE HAVE INFLAMMATORY DISEASES. > > S THAT DIFFICULT QUESTION BECAUSE THERE ARE ALL SORTS OF VARIABLES. GIVEN WHAT YOU SEED RIGHT NOW AND WHAT YOU’RE WORKING ON, WHAT WOULD BE YOUR BEST ASSESSMENT AS TO WHEN WILL WE BE ABLE TO CURE CANCER? > > I THINK CURE CANCER IS A MAVS STATEMENT BECAUSE IT’S A COLLECTION OF A HUGE NUMBER OF DISEASES. WE CAN SEE THIS AS A STEP-WISE PROCESS TOWARDS TAKE PEOPLE WITH DIFFERENT CANCERS AND GIVING THEM A HUGELY BET ERTZ OUTLOOK. WHERE IT BECOMES MORE OF A CHRONIC DISEASE. YOU MAY BE TAKE MEDICINE FOR LIFE BUT YOU HAVE A NORMAL LIFESPAN. WE ALREADY SEE THIS IN SOME CANCER IN WHERE MEDICAL TREATMENTS CAN GIVE YOU A NORMAL LIFESPAN. FOR ME THAT WOULD BE INCREDIBLE, RIGHT? CANCER IS NOT SOMETHING YOU WORRY ABOUT. IT’S JUST TO MAKE SURE YOU GET THE RIGHT TREATMENT. YOU MAY HAVE TO TAKE TREATMENT. BUT YOU HAVE A NORMAL LIFESPAN. > > BUT IN 10 YEARS’ TIME GIVEN WHAT YOU AND MAX ARE WORKING ON WHAT, DOES OUR WORLD OF MEDICINE LOOK LIKE FOR PEOPLE INTERACTING WITH MEDICINE, INTERACTS WITH DOCTORS, HAVING TO TAKE THERAPEUTICS? > > HOW DIFFERENT IS IT GOING TO LOOK IN TWO YEARS. > > IT’S DEAF TO TURN A TIME FRAME. BUT I CAN SEE A FUTURE WHERE YOU DON’T HAVE TO WORRY. YOU MIGHT GO TO YOUR -- MAYBE YOU’RE INTERACTING WITH SOME SORT OF A.I. TOOL THAT CAN HELP DIAGNOSE YOU AT THAT POINT. IT’S A MASSIVE AMBITION. I THINK IT’S AN EXCITING FUTURE WHERE WE CAN MAKE IT A BIG IMPACT. THAT’S WHAT GETS ME OUT OF BED. THINKING ABOUT HOW CAN I IMPACT PATIENT’S LIVES WITH WORK THAT WE DO. > > MAX JADABURG. AND THE C.E.O. TALKING TO ME ABOUT THE PLATFORM AND THEIR AMBITIONS. COMING UP, WE’LL STAY WITH THE RACE TO BEAT CANCER. WE’RE GOING TO HEAR ON A LEADING EXPERTS ON A.I. AND HEALTHCARE ON WHAT THE TECHNOLOGY MEANS AGAINST THAT DISEASE. THAT IS NEXT. THIS IS BLOOMBERG. > > WELCOME BACK TO BLOOMBERG TECH EUROPE. SO THE PHARMACEUTICAL INDUSTRY IS ALREADY BEING RESHAPED BY ARTIFICIAL INTELLIGENCE. BUT HOW FAR CAN THE TECH ACTUALLY GO AND HOW FAST? I SAT DOWN WITH THE DIRECTOR OF THE CAMBRIDGE CENTER FOR A.I. IN MEDICINE, MIHAELA VAN DER SCHAAR ON THE PROMISE AND THE PITFALLS OF A.I.-DRIVEN DRUG DISCOVERY. > > WELL, LET ME JUST SAY THAT THE TECHNOLOGY THAT ISOMORPHIC LABS ARE DEVELOPING AND MANY OTHERS, STARTUPS AND COMPANIES ARE DEVELOPING IS VERY EXCITING. HOWEVER, I DO THINK THAT WE NEED TO BE A LITTLE BIT CAUTIOUS BECAUSE IN ORDER TO COME UP WITH A MOLECULE THAT IS INDEED USEFUL AND WILL MAKE IT ALL THE WAY TO THE REGULATORY PROCESS IS ANOTHER THING. > > AND DATA IS ESSENTIAL TO THIS AND CLINICAL DATA, MEDICAL DATA CAN BE SEAL ODD, IT CAN BE BIASED, IT CAN BE VERY MESSY. THE MODELS ARE ONLY AS GOOD AS THE DATA THAT GOES INTO THEM. GOOD DATA IN. GOOD DATA OUT. HOW MUCH OF HURDLE IS DATA? > > DATA KEY. BUT THERE I AM VERY OPTIMISTIC. BECAUSE YES, THIS DATA IS MESSY. IT CONTAINS MISSING DATA. AND ALL OF THAT, THOUGH -- AND DATA MAY NEED TO BE HARMONIZED. BUT THIS IS WHERE A.I. CAN REALLY EXCEL. > > AND YOU’RE AN ACADEMIC. BUT YOU ALSO WORKED IN INDUSTRY AS WELL. YOU’VE GOT DOZENS OF PATENTS TO YOUR NAME. HOW DOES THIS TECHNOLOGY CHANGE THE BALANCE OF POWER FOR THE FARMER INDUSTRY? > > WELL, I THINK THAT WE MAY SEE VERY DIFFERENT NEW BRANDS OF -- OF FUTURE COMPANYS THAT WILL BUILD DRUGS. I THINK THAT INCREASINGLY THE PHARMACEUTICAL INDUSTRY IS JOINED BY THIS VERY NEW STARTUPS THAT ARE BUILDING MOLL MOLECULES, LABS. SO I DO THINK THE ENTIRE PROCESS WILL CHANGE. THERE ARE MANY DISEASES, CANCER INCLUDED WHERE WE DON’T HAVE THE MIRACLE DRUG. AND I HOPE THAT THIS COMPETITION IS GOING TO ENERGIZE EVERYBODY AND PROVIDE EXCITING NEW DRUGS THAT WILL BE SOLVING A LOT OF CURRENT DISEASES THAT FOR WHICH WE CAN’T HAVE A SOLUTION. > > DOES A CURE TO CANCER AS A RESULT OF A.I. DISCOVERED DRUGS, DOES THAT HAPPEN IN OUR LIFETIME? > > I NOPE HOPE SO. AGAIN, IT’S NOT JUST ABOUT DRUGS. IT’S ABOUT USING A GUY TO IDENTIFY DISEASE MUCH MORE EARLY. AND THEN FINDING THE RIGHT DRUG FOR THE RIGHT PERSON. > > MIHAELA VAN DER SCHAAR FROM THE CAMBRIDGE CENTER FOR AI IN MEDICINE ON THE NEXT EPISODE OF BLOOMBERG TECH EUROPE WE’RE GOING TO TAKE A DEEP DIVE TO SEE HOW ARTIFICIAL INTELLIGENCE IS CHANGING THE BANKING SECTOR. WE’RE INSIDE WITH SOME OF THE BIGGEST NAMES. WE’RE GOING TO LIFT THE LID ON HOW FIRMS ARE DEPLOYING A.I.

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How AI Company Isomorphic Labs Is Working to Solve All Disease | Bloomberg Tech: Europe 9/12/2025

AI-powered drug discovery: is it the next frontier of medicine? From cutting down costs, to speeding up development, the technology promises plenty - but can it deliver? In this episode, Bloomberg's Tom Mackenzie speaks exclusively to Demis Hassabis, the Nobel Laureate aiming to literally "solve all disease" through his work at London-based Isomorphic Labs. Hassabis' work comes in addition to his responsibilities at Alphabet Inc., where he oversees all of the company's core AI work as co-founder and CEO of Google DeepMind. --- "Bloomberg Tech: Europe" spotlights the biggest names and trends shaping the region's technology ecosystem as the global competition heats up. This monthly, 30-minute magazine-style show features in-depth interviews with top technology leaders, as well as major investors and policymakers - giving you a compelling A to Z of the most consequential innovations, opportunities and challenges. (Source: Bloomberg)