CryMonkey nag-retweet
CryMonkey
362 posts


ตอนนี้ทุกคนในประเทศไทยกินข้าวเย็นกันหมดแล้วหรือยัง?
อยากดูภาพว่าคนอื่นกินอะไรบ้าง😋😋😋
ขอให้ทุกคนมีความสุขในวันหยุดสุดสัปดาห์!

I'm Okay ⌘@ohlala573
いただきます( ◜‿◝ )♡ 今日もお疲れ様でした😋
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@chakidbest29 This energy is hitting different manifesting that July bag fr
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CryMonkey nag-retweet

From physical wellness to inner peace, yoga enriches every aspect of life. Delighted to join this year’s celebrations in Kolkata. twitter.com/i/broadcasts/1…
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@rola_almoghrabi @gazafunds @AnnieLaline @ariatzy_ @benson108620307 @David3131313 @ChevezRomario @decrescentc8n6 @DavidPa03067190 @ChevalierT43720 @Blaze_Knight95 Sending so much love and strength your way. This is heartbreaking.
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MY CHILD IS DYING😭
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I desperately need milk for my baby🍼
chuffed.org/project/safe-l…

Eileen's mother ❣🍉@rola_almoghrabi
I NEED MILK 🍼🍼 ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ we’ll remind you ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ that ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ I desperately need milk for my baby.🍼 chuffed.org/project/safe-l…
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CryMonkey nag-retweet
CryMonkey nag-retweet

NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
NO DONATIONS FOR FIVE DAYS!!
chuffed.org/project/186013…

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CryMonkey nag-retweet

A drug spends years in trials, then decades in the real world.
The real world generates far more evidence about how it actually performs than any trial.
That evidence rarely goes anywhere.
Which patients respond. What side effects emerge. How it behaves across populations the trial never tested.
The most valuable evidence in the entire lifecycle — and it almost never flows back into what gets discovered or trialed next.
Every new program starts from the same incomplete picture as the last.
AI can generate more candidates than ever. But a pipeline that can’t learn from its own history won’t produce a different outcome.
The missing infrastructure isn’t discovery. It’s the loop back.

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Don't skip
Help us in any way you can🙏🏾
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I desperately need milk for my baby.
gofundme.com/f/donate-to-he…

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@majid_9495 Heartbreaking stay strong mama sending love and support
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CryMonkey nag-retweet

@LifeNetwork_AI Exactly
Faster tools in a broken sequential system still leave us waiting
The real leap will come from rethinking the entire parallel, integrated structure of drug development
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CryMonkey nag-retweet

I NEED MILK 🍼🍼
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we’ll remind you
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I desperately need milk for my baby.🍼
chuffed.org/project/safe-l…

Eileen's mother ❣🍉@rola_almoghrabi
MY CHILD IS DYING😭 ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ we’ll remind you ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ that ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ ︎ I desperately need milk for my baby🍼 chuffed.org/project/safe-l…
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CryMonkey nag-retweet

In the last 30 years, computing power has increased by a factor of a trillion.
Yet developing a new therapy remains one of the slowest, most expensive, and most failure-prone processes in modern science.
This is the paradox worth understanding.
AI has accelerated target identification. Gene sequencing has collapsed from years to days. Computational modeling can simulate molecular interactions at a scale that was unimaginable a decade ago.
Yet the pipeline moves at the same pace.
The reason is that technology has made individual stages of the process faster. What it has not changed is the structure of the process itself.
Drug development is still sequential. Each stage waits for the one before it. Each program still assembles its own evidence infrastructure from scratch. The handoff between controlled validation and real-world performance still happens after approval.
Better tools applied to a fragmented, sequential process produce better science at the same speed.
What compresses the timeline is not faster tools inside the existing structure. It is a different structure entirely.

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CryMonkey nag-retweet

AI solving candidate generation at massive scale while validation, trials, and real-world evidence infrastructure stay slow is the accurate diagnosis.
More molecules in the queue doesn’t translate to more therapies reaching patients if the downstream process still takes years and hundreds of millions per success. The real leverage now sits in tools and infrastructure that compress validation timelines and generate reliable evidence faster — not in generating even more hypotheses that then sit in the same slow pipeline.
Discovery got the AI upgrade first. Development and validation infrastructure is the next structural bottleneck worth solving.
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CryMonkey nag-retweet
CryMonkey nag-retweet








