The Impact of AI in the World of Science Tutorial

Discover how AI can transform the world of science. This video presents the impact of AI in the scientific field, and explores the various ways this technology can optimize research processes, improve outcomes and solve complex problems in the pharmaceutical sector.

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Objectifs :

This document aims to provide a comprehensive overview of the transformative impact of Generative AI in drug design, highlighting its benefits, challenges, and future potential in the pharmaceutical industry.

Chapitres :

  1. Introduction to Drug Design
    The field of drug design is vital for human health, traditionally characterized by lengthy and costly processes. Developing a new drug can take between 10 to 15 years and may cost up to $2.6 billion due to extensive experimentation and clinical trials.
  2. The Role of Generative AI
    Generative AI is revolutionizing drug design by enabling the prediction of the biological activity of molecules with over 90% accuracy. This technology has significantly reduced the time required for molecule design by 70%, leading to faster identification of potential drug candidates.
  3. Impact on Laboratory Testing
    The integration of Generative AI has resulted in a 50% reduction in laboratory testing through digital simulations. Additionally, there is a 40% decrease in the reliance on traditional screening methods, allowing researchers to identify drug candidates three times faster.
  4. Clinical Phase Improvements
    Generative AI has also contributed to a 30% decrease in failures during the clinical phase of drug development. These advancements lead to a 40% reduction in preclinical phase costs and a 25% acceleration in the market launch of new drugs.
  5. Financial Implications
    The efficiencies gained through Generative AI could potentially save pharmaceutical companies up to $1 billion over the lifetime of a drug. However, the initial investment in AI technology can be substantial, reaching up to $10 million.
  6. Challenges and Considerations
    Despite its advantages, there are challenges associated with Generative AI in drug design. There is a 5% risk that AI may overlook certain side effects, emphasizing the need for human vigilance and oversight in the drug development process.
  7. Future Prospects
    As Generative AI continues to evolve, it holds the promise of further reducing costs and timeframes in drug design. This evolution could open new avenues for the future of medicine, enhancing the efficiency and effectiveness of drug development.
  8. Conclusion
    Generative AI is redefining the landscape of drug design, offering a faster and more economical approach to developing new medications. While the technology presents significant benefits, it is crucial to maintain human oversight to ensure safety and efficacy in drug development.

FAQ :

What is Generative AI in drug design?

Generative AI refers to artificial intelligence systems that can create new predictions or content based on existing data. In drug design, it is used to predict the biological activity of molecules, significantly speeding up the drug development process.

How does Generative AI reduce drug development costs?

Generative AI reduces drug development costs by decreasing the time required for molecule design by 70%, leading to a 40% reduction in preclinical phase costs and a potential saving of $1 billion for pharmaceutical companies over a drug's lifetime.

What are the risks associated with using AI in drug design?

While Generative AI offers many benefits, there are risks, including initial costs that can reach $10 million and a 5% chance that AI might overlook certain side effects of drugs.

How much time does Generative AI save in drug design?

Generative AI can reduce the time for molecule design by 70%, allowing researchers to identify drug candidates three times faster than traditional methods.

What is the significance of the 30% decrease in clinical phase failures?

A 30% decrease in failures during the clinical phase means that fewer drug candidates fail in trials, which can lead to more successful drug launches and better resource allocation in the pharmaceutical industry.

Quelques cas d'usages :

Accelerating Drug Discovery

Pharmaceutical companies can utilize Generative AI to streamline the drug discovery process, allowing them to identify viable drug candidates much faster than traditional methods, thus improving their research and development timelines.

Cost Reduction in Drug Development

By implementing Generative AI, companies can significantly cut down on the costs associated with the preclinical phase of drug development, potentially saving millions in research expenses.

Enhancing Clinical Trial Success Rates

With the ability to predict biological activity and reduce failures, Generative AI can help improve the success rates of clinical trials, leading to more effective treatments reaching the market.

Improving Safety Assessments

Generative AI can assist researchers in better understanding potential side effects of new drugs, thereby enhancing safety assessments and ensuring that drugs are safer for public use.

Optimizing Resource Allocation

By reducing the time and costs associated with drug design, Generative AI allows pharmaceutical companies to allocate resources more effectively, focusing on the most promising drug candidates.

Glossaire :

Generative AI

A type of artificial intelligence that can generate new content or predictions based on existing data, particularly useful in drug design for predicting the biological activity of molecules.

Drug Design

The process of discovering and developing new medications, which traditionally involves extensive experimentation and clinical trials.

Biological Activity

The effect a substance has on living organisms, which is crucial for determining the efficacy of a drug.

Clinical Trials

Research studies performed on people to evaluate the effectiveness and safety of a new drug or treatment.

Preclinical Phase

The stage of drug development that occurs before clinical trials, involving laboratory and animal studies to assess the safety and biological activity of a drug.

Digital Simulation

The use of computer models to replicate and study the behavior of biological systems, which helps in reducing laboratory testing.

Traditional Screening Methods

Conventional techniques used to identify potential drug candidates, often involving extensive laboratory testing.

Side Effects

Unintended effects of a drug that can occur alongside the desired therapeutic effects.

résultat(s)
00:00:05
Generative AI in drug Design A
00:00:07
Revolution in progress The field
00:00:09
of drug design has always been
00:00:11
crucial for human health.
00:00:13
But did you know that its traditional
00:00:16
method can cost up to $2.6 billion
00:00:19
for a new drug for decades?
00:00:21
Developing a drug could take 10 to 15 years,
00:00:24
requiring intensive experimentation
00:00:26
and clinical trials.
00:00:27
Generative AI is transforming this landscape.
00:00:29
It allows for the prediction of the
00:00:32
biological activity of molecules with
00:00:34
over 90% accuracy and has reduced
00:00:36
the time for molecule design by 70%.
00:00:39
The result?
00:00:40
A 50% reduction in laboratory
00:00:42
testing thanks to digital simulation
00:00:44
and a 40% decrease in the use of
00:00:48
traditional screening methods,
00:00:49
researchers can now identify drug
00:00:51
candidates three times faster.
00:00:53
And the best part,
00:00:54
a 30% decrease in failures during
00:00:57
the clinical phase.
00:00:58
These advances translate into a 40%
00:01:00
reduction in preclinical phase costs
00:01:02
and a 25% acceleration in market launch.
00:01:05
Potentially,
00:01:06
this represents a saving of $1
00:01:09
billion for pharmaceutical companies
00:01:11
over the lifetime of a drug.
00:01:13
However, not everything is perfect.
00:01:15
The initial costs for AI can
00:01:17
reach $10 million,
00:01:18
and there's a 5% risk that AI
00:01:21
might miss certain side effects.
00:01:23
Generative AI is redefining drug design,
00:01:25
promising a faster and more
00:01:27
economical future.
00:01:28
As AI evolves,
00:01:29
it could further reduce costs
00:01:31
and time frames,
00:01:32
opening new prospects for
00:01:34
the medicine of the future.
00:01:36
But human vigilance and
00:01:38
oversight remain essential.

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résultat(s)
00:00:05
IA generativa no design de fármacos A
00:00:07
Revolução em curso O campo
00:00:09
de design de fármacos sempre foi
00:00:11
crucial para a saúde humana.
00:00:13
Mas sabia que o seu tradicional
00:00:16
método pode custar até US$ 2,6 bilhões
00:00:19
para um novo medicamento há décadas?
00:00:21
O desenvolvimento de um medicamento pode demorar 10 a 15 anos,
00:00:24
que requerem experimentação intensiva
00:00:26
e ensaios clínicos.
00:00:27
A IA generativa está a transformar este cenário.
00:00:29
Permite a previsão do
00:00:32
atividade biológica de moléculas com
00:00:34
mais de 90% de precisão e reduziu
00:00:36
o tempo de conceção das moléculas é de 70%.
00:00:39
O resultado?
00:00:40
Uma redução de 50% no laboratório
00:00:42
Testes graças à simulação digital
00:00:44
e uma diminuição de 40% na utilização de
00:00:48
métodos tradicionais de rastreio,
00:00:49
Investigadores podem agora identificar fármaco
00:00:51
candidatos três vezes mais rápidos.
00:00:53
E a melhor parte,
00:00:54
uma diminuição de 30% nas falhas durante
00:00:57
a fase clínica.
00:00:58
Estes avanços traduzem-se num aumento de 40%
00:01:00
redução dos custos da fase pré-clínica
00:01:02
e uma aceleração de 25% no lançamento no mercado.
00:01:05
Potencialmente,
00:01:06
Isso representa uma economia de $1
00:01:09
mil milhões para as empresas farmacêuticas
00:01:11
ao longo da vida de uma droga.
00:01:13
No entanto, nem tudo é perfeito.
00:01:15
Os custos iniciais da IA podem
00:01:17
atingir $10 milhões,
00:01:18
e há um risco de 5% de que a IA
00:01:21
pode falhar certos efeitos secundários.
00:01:23
A IA generativa está redefinindo o design de medicamentos,
00:01:25
prometendo um mais rápido e mais
00:01:27
futuro económico.
00:01:28
À medida que a IA evolui,
00:01:29
Poderia reduzir ainda mais os custos
00:01:31
e prazos,
00:01:32
abrir novas perspetivas para
00:01:34
a medicina do futuro.
00:01:36
Mas a vigilância humana e
00:01:38
a supervisão continua a ser essencial.

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résultat(s)
00:00:05
IA generativa nella progettazione di farmaci A
00:00:07
Rivoluzione in corso Il campo
00:00:09
del design dei farmaci è sempre stato
00:00:11
fondamentale per la salute umana.
00:00:13
Ma lo sapevi che è tradizionale
00:00:16
il metodo può costare fino a 2,6 miliardi di dollari
00:00:19
per un nuovo farmaco per decenni?
00:00:21
Lo sviluppo di un farmaco potrebbe richiedere dai 10 ai 15 anni,
00:00:24
che richiede una sperimentazione intensiva
00:00:26
e sperimentazioni cliniche.
00:00:27
L'intelligenza artificiale generativa sta trasformando questo panorama.
00:00:29
Consente la previsione del
00:00:32
attività biologica di molecole con
00:00:34
precisione superiore al 90% e ridotta
00:00:36
il tempo necessario per la progettazione delle molecole del 70%.
00:00:39
Il risultato?
00:00:40
Una riduzione del 50% del numero di laboratori
00:00:42
test grazie alla simulazione digitale
00:00:44
e una riduzione del 40% nell'uso di
00:00:48
metodi di screening tradizionali,
00:00:49
i ricercatori possono ora identificare il farmaco
00:00:51
i candidati tre volte più velocemente.
00:00:53
E la parte migliore,
00:00:54
una riduzione del 30% dei guasti durante
00:00:57
la fase clinica.
00:00:58
Questi progressi si traducono in un 40%
00:01:00
riduzione dei costi della fase preclinica
00:01:02
e un'accelerazione del 25% nel lancio sul mercato.
00:01:05
Potenzialmente,
00:01:06
ciò rappresenta un risparmio di 1 dollaro
00:01:09
miliardo per le aziende farmaceutiche
00:01:11
nel corso della durata di vita di un farmaco.
00:01:13
Tuttavia, non tutto è perfetto.
00:01:15
I costi iniziali per l'IA possono
00:01:17
raggiungere i 10 milioni di dollari,
00:01:18
e c'è un rischio del 5% che l'IA
00:01:21
potrebbero mancare alcuni effetti collaterali.
00:01:23
L'intelligenza artificiale generativa sta ridefinendo il design dei farmaci,
00:01:25
promettendo una soluzione più veloce e di più
00:01:27
futuro economico.
00:01:28
Man mano che l'IA si evolve,
00:01:29
potrebbe ridurre ulteriormente i costi
00:01:31
e tempistiche,
00:01:32
aprendo nuove prospettive per
00:01:34
la medicina del futuro.
00:01:36
Ma la vigilanza umana e
00:01:38
la supervisione rimane essenziale.

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résultat(s)
00:00:05
Генеративный искусственный интеллект в разработке лекарств A
00:00:07
Незавершенная революция В этой области
00:00:09
дизайн лекарств всегда был
00:00:11
крайне важно для здоровья человека.
00:00:13
Но знаете ли вы, что это традиционное блюдо
00:00:16
метод может стоить до 2,6 миллиарда долларов
00:00:19
за новый препарат на протяжении десятилетий?
00:00:21
Разработка препарата может занять от 10 до 15 лет,
00:00:24
требующий интенсивных экспериментов
00:00:26
и клинические испытания.
00:00:27
Генеративный искусственный интеллект меняет этот ландшафт.
00:00:29
Это позволяет прогнозировать
00:00:32
биологическая активность молекул с
00:00:34
точность более 90% и снизилась
00:00:36
время проектирования молекул на 70%.
00:00:39
Результат?
00:00:40
Сокращение лабораторных затрат на 50%
00:00:42
тестирование благодаря цифровому моделированию
00:00:44
и сокращение использования на 40%
00:00:48
традиционные методы скрининга,
00:00:49
теперь исследователи могут идентифицировать лекарство
00:00:51
кандидаты в три раза быстрее.
00:00:53
И что самое приятное,
00:00:54
снижение количества отказов на 30% во время
00:00:57
клиническая фаза.
00:00:58
Эти достижения составляют 40%
00:01:00
снижение затрат на доклиническую фазу
00:01:02
и ускорение вывода продукции на рынок на 25%.
00:01:05
Потенциально
00:01:06
это означает экономию в размере 1 долл. США
00:01:09
миллиард для фармацевтических компаний
00:01:11
в течение всего срока службы лекарственного препарата.
00:01:13
Однако не все идеально.
00:01:15
Первоначальные затраты на искусственный интеллект могут
00:01:17
достигать 10 миллионов долларов,
00:01:18
и риск того, что искусственный интеллект составит 5%
00:01:21
может пропустить некоторые побочные эффекты.
00:01:23
Генеративный искусственный интеллект переопределяет дизайн лекарств,
00:01:25
обещает работать быстрее и эффективнее
00:01:27
экономичное будущее.
00:01:28
По мере развития искусственного интеллекта
00:01:29
это может еще больше снизить затраты
00:01:31
и сроки,
00:01:32
открывая новые перспективы для
00:01:34
медицина будущего.
00:01:36
Но человеческая бдительность и
00:01:38
надзор по-прежнему необходим.

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résultat(s)
00:00:05
IA generativa en el diseño de fármacos A
00:00:07
Revolución en progreso El campo
00:00:09
del diseño de fármacos siempre ha sido
00:00:11
crucial para la salud humana.
00:00:13
¿Pero sabías que es tradicional
00:00:16
este método puede costar hasta 2.600 millones de dólares
00:00:19
para un nuevo medicamento durante décadas?
00:00:21
Desarrollar un medicamento puede llevar de 10 a 15 años,
00:00:24
lo que requiere una experimentación intensiva
00:00:26
y ensayos clínicos.
00:00:27
La IA generativa está transformando este panorama.
00:00:29
Permite la predicción de
00:00:32
actividad biológica de las moléculas con
00:00:34
más del 90% de precisión y se ha reducido
00:00:36
el tiempo necesario para el diseño de moléculas en un 70%.
00:00:39
¿El resultado?
00:00:40
¿Una reducción del 50% en el laboratorio
00:00:42
pruebas gracias a la simulación digital
00:00:44
y una disminución del 40% en el uso de
00:00:48
métodos de cribado tradicionales,
00:00:49
los investigadores ahora pueden identificar el fármaco
00:00:51
candidatos tres veces más rápido.
00:00:53
Y la mejor parte,
00:00:54
una disminución del 30% en el número de fallos durante
00:00:57
la fase clínica.
00:00:58
Estos avances se traducen en un 40%
00:01:00
reducción de los costes de la fase preclínica
00:01:02
y una aceleración del 25% en el lanzamiento al mercado.
00:01:05
Potencialmente,
00:01:06
esto representa un ahorro de 1 dólar
00:01:09
mil millones para las compañías farmacéuticas
00:01:11
durante la vida útil de un medicamento.
00:01:13
Sin embargo, no todo es perfecto.
00:01:15
Los costos iniciales de la IA pueden
00:01:17
alcanzar los 10 millones de dólares,
00:01:18
y hay un riesgo del 5% de que la IA
00:01:21
podría pasar por alto ciertos efectos secundarios.
00:01:23
La IA generativa está redefiniendo el diseño de fármacos,
00:01:25
prometiendo una solución más rápida y
00:01:27
futuro económico.
00:01:28
A medida que la IA evoluciona,
00:01:29
podría reducir aún más los costos
00:01:31
y plazos,
00:01:32
abriendo nuevas perspectivas para
00:01:34
la medicina del futuro.
00:01:36
Pero la vigilancia humana y
00:01:38
la supervisión sigue siendo esencial.

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résultat(s)
00:00:05
Generatieve AI in geneesmiddelenontwerp A
00:00:07
Revolutie aan de gang Het veld
00:00:09
van medicijnontwerp is altijd
00:00:11
cruciaal voor de menselijke gezondheid.
00:00:13
Maar wist je dat het traditioneel is?
00:00:16
methode kan tot $2,6 miljard kosten
00:00:19
voor een nieuw medicijn voor decennia?
00:00:21
Het ontwikkelen van een medicijn kan 10 tot 15 jaar duren,
00:00:24
waarvoor intensief moet worden geëxperimenteerd
00:00:26
en klinische onderzoeken.
00:00:27
Generatieve AI transformeert dit landschap.
00:00:29
Het maakt de voorspelling mogelijk van de
00:00:32
biologische activiteit van moleculen met
00:00:34
meer dan 90% nauwkeurigheid en is verminderd
00:00:36
de tijd voor molecuulontwerp met 70%.
00:00:39
Het resultaat?
00:00:40
Een reductie van 50% in het laboratorium
00:00:42
testen dankzij digitale simulatie
00:00:44
en een afname van 40% in het gebruik van
00:00:48
traditionele screeningsmethoden,
00:00:49
onderzoekers kunnen nu medicijnen identificeren
00:00:51
kandidaten drie keer sneller.
00:00:53
En het beste deel,
00:00:54
een afname van 30% van het aantal storingen tijdens
00:00:57
de klinische fase.
00:00:58
Deze vooruitgang vertaalt zich in een 40%
00:01:00
verlaging van de kosten van de preklinische fase
00:01:02
en een versnelling van 25% in de marktintroductie.
00:01:05
Potentieel,
00:01:06
dit betekent een besparing van $1
00:01:09
miljard voor farmaceutische bedrijven
00:01:11
gedurende de levensduur van een geneesmiddel.
00:01:13
Niet alles is echter perfect.
00:01:15
De initiële kosten voor AI kunnen
00:01:17
$10 miljoen bereiken,
00:01:18
en er is een risico van 5% dat AI
00:01:21
kan bepaalde bijwerkingen missen.
00:01:23
Generatieve AI herdefinieert het medicijnontwerp,
00:01:25
belooft een snellere en meer
00:01:27
economische toekomst.
00:01:28
Naarmate AI evolueert,
00:01:29
het zou de kosten verder kunnen verlagen
00:01:31
en tijdsbestekken,
00:01:32
het openen van nieuwe perspectieven voor
00:01:34
het medicijn van de toekomst.
00:01:36
Maar menselijke waakzaamheid en
00:01:38
toezicht blijft essentieel.

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résultat(s)
00:00:05
Generatywna sztuczna inteligencja w projektowaniu leków A
00:00:07
Rewolucja w toku Pole
00:00:09
projektowanie leków zawsze było
00:00:11
kluczowe dla zdrowia ludzkiego.
00:00:13
Ale czy wiesz, że jest to tradycyjne
00:00:16
Metoda może kosztować do 2,6 miliarda dolarów
00:00:19
na nowy lek przez dziesięciolecia?
00:00:21
Opracowanie leku może zająć od 10 do 15 lat,
00:00:24
wymagające intensywnych eksperymentów
00:00:26
i badania kliniczne.
00:00:27
Generatywna sztuczna inteligencja zmienia ten krajobraz.
00:00:29
Pozwala na przewidywanie
00:00:32
aktywność biologiczna cząsteczek z
00:00:34
ponad 90% dokładności i zmniejszyła się
00:00:36
czas projektowania cząsteczki o 70%.
00:00:39
Rezultat?
00:00:40
50% redukcja w laboratorium
00:00:42
testowanie dzięki symulacji cyfrowej
00:00:44
i 40% spadek wykorzystania
00:00:48
tradycyjne metody badań przesiewowych,
00:00:49
Naukowcy mogą teraz zidentyfikować narkotyki
00:00:51
Kandydaci trzy razy szybciej.
00:00:53
I najlepsza część,
00:00:54
spadek o 30% awarii podczas
00:00:57
fazy klinicznej.
00:00:58
Te postępy przekładają się na 40%
00:01:00
zmniejszenie kosztów fazy przedklinicznej
00:01:02
i 25% przyspieszenie wprowadzenia na rynek.
00:01:05
Potencjalnie,
00:01:06
oznacza to oszczędność w wysokości 1 USD
00:01:09
Miliard dla firm farmaceutycznych
00:01:11
przez całe życie narkotyku.
00:01:13
Jednak nie wszystko jest idealne.
00:01:15
Początkowe koszty sztucznej inteligencji mogą
00:01:17
osiągnąć 10 milionów dolarów,
00:01:18
i istnieje 5% ryzyko, że sztuczna inteligencja
00:01:21
może pominąć pewne skutki uboczne.
00:01:23
Generatywna sztuczna inteligencja na nowo definiuje projektowanie leków,
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obiecując szybciej i więcej
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ekonomiczna przyszłość.
00:01:28
W miarę ewolucji sztucznej inteligencji,
00:01:29
Może to jeszcze bardziej obniżyć koszty
00:01:31
i ramy czasowe,
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otwieranie nowych perspektyw
00:01:34
Medycyna przyszłości.
00:01:36
Ale ludzka czujność i
00:01:38
Nadzór pozostaje niezbędny.

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résultat(s)
00:00:05
Generatív AI a gyógyszertervezésben A
00:00:07
Forradalom folyamatban A terület
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a gyógyszertervezés mindig is volt
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kulcsfontosságú az emberi egészség szempontjából.
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De tudtad, hogy a hagyományos
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A módszer akár 2,6 milliárd dollárba is kerülhet
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évtizedekig egy új gyógyszerért?
00:00:21
Egy gyógyszer kifejlesztése 10-15 évig tarthat,
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intenzív kísérletezést igényel
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és klinikai vizsgálatok.
00:00:27
A generatív AI átalakítja ezt a tájat.
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Lehetővé teszi a
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molekulák biológiai aktivitása
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több mint 90% -os pontosság és csökkent
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a molekulák tervezésének ideje 70% -kal.
00:00:39
Az eredmény?
00:00:40
50% -os csökkentés a laboratóriumban
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tesztelés a digitális szimulációnak köszönhetően
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és 40% -kal csökkent a felhasználás
00:00:48
hagyományos szűrőmódszerek,
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A kutatók most azonosíthatják a drogot
00:00:51
Háromszor gyorsabban jelentkeznek.
00:00:53
És a legjobb rész,
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a meghibásodások 30% -kal csökkenése
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a klinikai fázis.
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Ezek az előrelépések 40% -ot eredményeznek
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a preklinikai fázis költségeinek csökkentése
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és 25% -os gyorsulás a piaci bevezetésben.
00:01:05
Potenciálisan,
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ez 1 dolláros megtakarítást jelent
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Milliárd a gyógyszeripari vállalatok számára
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egy gyógyszer élettartama alatt.
00:01:13
Azonban nem minden tökéletes.
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Az AI kezdeti költségei lehetnek
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elérheti a 10 millió dollárt,
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és 5% -os kockázata van annak, hogy az AI
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hiányozhat bizonyos mellékhatásokat.
00:01:23
A generatív AI újradefiniálja a gyógyszertervezést,
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gyorsabban és többet ígér
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Gazdasági jövő.
00:01:28
Ahogy az AI fejlődik,
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Ez tovább csökkentheti a költségeket
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és időkeretek,
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új kilátásokat nyit meg
00:01:34
A jövő gyógyszere.
00:01:36
De az emberi éberség és
00:01:38
A felügyelet továbbra is elengedhetetlen.

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Mandarine AI: CE QUI POURRAIT VOUS INTÉRESSER

RELATED COURSES This tutorial is part of the following courses

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Part 03 - Case Studies and Analysis

Discover the revolutionary potential of generative AI through diverse and concrete case studies illustrating its impact on various jobs with...

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