인생에 도움이 되는 바이오 영상 모음집
https://youtube.com/@Iamoneriver
바이오 시그널 랩에서 원리버와 함께하기
https://fanding.kr/@iamoneriver/membership/plan/9099/
문의
[email protected]
해당 채널의 게시물은 단순 의견 및 기록용도이고 매수-매도 등 투자권유를 의미하지 않습니다. 해당 게시물의 내용은 부정확할 수 있으며 매매에 따른 손실은 거래 당사자의 책임입
Created
7 November 2021 — measured — cross-checked against a third-party dataset (ext.tg_channel)
Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 67% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
32 measurements spanning 43 days, net +32. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 29,781–30,039 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
19 Sept 2026, 08:41
29,843
-27
16 Sept 2026, 23:39
29,870
-15
13 Sept 2026, 15:18
29,885
-8
11 Sept 2026, 18:42
29,893
-21
9 Sept 2026, 07:39
29,914
-26
5 Sept 2026, 23:42
29,940
-1
3 Sept 2026, 19:58
29,941
-14
2 Sept 2026, 10:44
29,955
+2
1 Sept 2026, 08:36
29,953
-10
31 Aug 2026, 05:44
29,963
-8
30 Aug 2026, 02:58
29,971
-9
29 Aug 2026, 04:07
29,980
+1
28 Aug 2026, 03:34
29,979
-12
27 Aug 2026, 03:44
29,991
-4
26 Aug 2026, 00:35
29,995
-6
25 Aug 2026, 01:52
30,001
-8
23 Aug 2026, 17:47
30,009
+8
22 Aug 2026, 04:48
30,001
+9
21 Aug 2026, 00:07
29,992
+5
20 Aug 2026, 01:47
29,987
first reading
Engagement
391 posts held, back to 5 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 70 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
15.2%
avg views ÷ 29,843 subscribers
Avg views / post
4,540
170 posts measured
Reaction rate
0.367%
reactions ÷ views · ER floor
Posts in window
174
of 391 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 164 of 170 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 24 September 2026
Posts held
391 (5 August 2026 – 24 September 2026)
Views total
771,330
Reactions total
2,730
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
24 Sept 2026, 16:30 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
≈1,770
Videos
≈10
Links
≈6,830
Lifetime counters from Telegram’s own channel header, read 24 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Reaction mix
7,525 reactions across 369 posts, in 12 distinct kinds. The most used accounts for 40.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
3,074
40.9%
👍
1,678
22.3%
🤯
1,394
18.5%
😱
657
8.73%
💊
165
2.19%
👌
161
2.14%
🥰
120
1.59%
🤩
101
1.34%
😍
74
0.983%
🕊
43
0.571%
✍
38
0.505%
❤🔥
20
0.266%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 374 of the 391 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 7,525 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 391 most recent posts we hold, published 5 August 2026 to 24 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
102
across the posts below
Posts paid on
3
of 384 we hold a reading for · 0.8%
Most on one post
100
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @pharmbiohana. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 391 most recent posts we hold for this entry, published 5 August 2026 to 24 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
(‘임상 단계’ AI 기반 천연물 유래 신약 개발사, Enveda, $311M 투자유치)
==================
AI 기반 천연물 유래 신약 개발사, Enveda Biosciences가 $311M 규모의 Series E 투자 유치를 완료하였다.
Enveda는 AI를 활용하여 천연물 생체 활성 물질을 발굴하는 플랫폼 기술을 보유하고 있고, 3개의 파이프라인이 임상 단계이다.
첫번째 파이프라인인 ENV-294은 경구용 아토피 및 천식 치료제이며, 분자 접착제(Non-degrading molecular glue/LOCKTAC)이다. 이 제품은 Rac2와 RhoGDI의 결합을 저해하여 Rac2 활성을 조절하고 TSLP 발현을 억제한다. 임상 1b상에서 습진 영역 및 중증도 지수(EASI)를 평균 85% 감소시키는 고무적인 효능 신호…
HLB, 항암신약 첫 FDA 승인…리라푸그라티닙, 담관암 치료제 허가
대한민국 제약·바이오 산업 130년 역사상 처음으로 국내 기업 계열의 항암 신약이 미국 식품의약국(FDA)의 허가를 받았다. HLB(028300)의 표적항암제 리라푸그라티닙(Lyrfigtu)이 FGFR2 유전자 융합 또는 재배열을 가진 절제 불가능·국소 진행성·전이성 담관암 환자 치료제로 FDA 승인을 획득했다.
https://markettimes.co.kr/?p=1952
Immunovant, IMVT-1402 CLE 임상 실패
IMVT-1402의 피부 홍반성 루푸스(CLE) PoC 임상이 1차 평가변수를 충족하지 못하면서 Immunovant가 해당 적응증 개발을 중단합니다.
57명을 대상으로 IMVT-1402 600mg을 주 1회 투여했고, 12주차 CLASI-A 변화율을 위약과 비교했는데 통계적 유의성을 확보하지 못했습니다.
다만 완전히 약효가 없었던 것은 아닙니다. 여러 지표에서 IMVT-1402 쪽으로 수치상 개선 경향이 있었고, IgG를 더 깊게 낮춘 환자일수록 실제 임상 반응도 좋아지는 경향은 확인됐습니다. 안전성 문제도 없었습니다.
그럼에도 회사가 구체적인 효과 크기나 p-value를 공개하지 않았고, “competitive landscape와 임상 결과를 고려해 내부 개발 기준을 충족하지 …
AZ 등 주요 9개 제약사, 유럽 제약산업 위기 공개 경고
제약산업, 국방·에네지 분야처럼 ‘국가 안보 자산’ 다룰 것 촉구
예방·진단·치료 역량 강화 의료시스템 현대화 등 모두 정부 몫“ https://www.yakup.com/news/index.html?mode=view&cat=12&nid=332944
프로티나의 기술적 해자는 AI 모델 자체가 아니라 SPID(Single-molecule Protein Interaction Detection)에 있습니다.
AI는 결국 좋은 데이터를 얼마나 많이, 얼마나 정확하게 학습하느냐가 중요한데요. 프로티나는 단백질-단백질 상호작용(PPI)을 단일분자 수준에서 직접 측정하고 정량화할 수 있는 SPID 플랫폼을 자체적으로 구축해왔습니다. Pi-Chip, Pi-View, Pi-InSight까지 하드웨어와 분석 체계를 직접 개발했고, 이를 통해 항체와 항원이 실제로 얼마나 잘 결합하는지 대규모로 실험 검증할 수 있습니다.
왜 이게 중요할까요?
AI가 발전할수록 ‘후보물질을 설계하는 능력’ 자체는 점점 상향 평준화될 가능성이 높기 때문입니다. AI가 수만~수십만 개의 항체 서열을 빠르게 제안할 수 있게 …
안녕하세요.
알테오젠의 ALT-B4와 MSD의 펨브롤리주맙을 결합한 피하주사 제형 관련 조성물 특허가 유럽특허청(EPO)에 등록됐습니다.
미국에 이어 유럽에서도 조성물 특허를 확보하며 키트루다 SC™의 지식재산권 보호 기반을 확대했습니다. 이번 유럽 특허의 존속기간은 2040년까지이며, 추가적 보호증명(SPC)을 통한 기간 연장도 가능합니다.
알테오젠은 물질·조성물·제조·고정용량복합제 관련 특허 포트폴리오를 지속적으로 강화해 하이브로자임 플랫폼 파트너의 안정적인 사업화를 뒷받침하겠습니다.
[보도자료] https://alteogen.com/kr/sub/ir/news.php?mode=view&bid=1&idx=373&page=1
Intuitive Surgical da Vinci 5의 성인 심장수술에 대한 유럽 CE Mark 획득을 발표
로봇을 심장수술까지 포함하는 범용 플랫폼으로 확장하는 전략이 실제 규제 허가로 진행되고 있는 것
https://news.cision.com/se/intuitive-surgical-nordics/r/da-vinci-5-erhaller-ce-markning-for-hjartkirurgi,c4399028
최근 10년
추석 명절 연휴 전
코스피 지수 평균 -0.03%
코스닥 지수 평균 -0.35%
추석 명절 연휴 후
코스피 지수 평균 +1.09%
코스닥 지수 평균 +0.10%
❤7👍3🤯1
Showing the 12 most recent of 391 posts we hold for @pharmbiohana. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 391 most recent posts we hold, published 5 August 2026 to 24 September 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
유해섹터 인겜미 @tteoksangMalangCow · 69 (as read 7 September 2026)#89
Read from Telegram’s recommendation API, most recently 7 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
YM리서치 @ym_research · 40,010 Telegram ranks this channel #4 of 89 here — alongside 88 others — read 2 September 2026
가치투자클럽 @corevalue · 67,564 Telegram ranks this channel #9 of 93 here — alongside 92 others — read 2 September 2026
허혜민의 제약/바이오 소식통 @huhpharm · 24,282 Telegram ranks this channel #17 of 93 here — alongside 92 others — read 16 September 2026
도PB의 생존투자 @survival_DoPB · 22,275 Telegram ranks this channel #19 of 90 here — alongside 89 others — read 21 September 2026
Yeouido Lab_여의도 톺아보기 @Yeouido_Lab · 43,309 Telegram ranks this channel #20 of 90 here — alongside 89 others — read 2 September 2026
루팡 @bornlupin · 48,016 Telegram ranks this channel #23 of 91 here — alongside 90 others — read 2 September 2026
조기주식회 공부방 @EarlyStock1 · 24,432 Telegram ranks this channel #25 of 91 here — alongside 90 others — read 16 September 2026
김찰저의 관심과 생각 저장소 @kimcharger · 24,877 Telegram ranks this channel #25 of 88 here — alongside 87 others — read 15 September 2026
재야의 고수들 @gaoshoukorea · 41,159 Telegram ranks this channel #26 of 90 here — alongside 89 others — read 2 September 2026
시장 이야기 by 제이슨 @bumgore · 35,332 Telegram ranks this channel #30 of 89 here — alongside 88 others — read 2 September 2026
Buff @bufkr · 22,258 Telegram ranks this channel #31 of 89 here — alongside 88 others — read 21 September 2026
유진투자증권 코스닥벤처팀 @SmallCap · 23,201 Telegram ranks this channel #31 of 96 here — alongside 95 others — read 19 September 2026
HS아카데미 대표 이효석 @HS_academy · 36,249 Telegram ranks this channel #35 of 90 here — alongside 89 others — read 8 September 2026
주식 급등일보🚀급등테마·대장주 탐색기 | Korean Stocks @FastStockNews · 128,921 Telegram ranks this channel #36 of 92 here — alongside 91 others — read 2 September 2026
하나 중국/신흥국 전략 김경환 @HANAchina · 35,284 Telegram ranks this channel #43 of 92 here — alongside 91 others — read 2 September 2026
피카츄 아저씨⚡️ @pikachu_aje · 25,242 Telegram ranks this channel #44 of 91 here — alongside 90 others — read 14 September 2026
이지스스트레티지 리서치 @jeilstock · 26,472 Telegram ranks this channel #46 of 93 here — alongside 92 others — read 12 September 2026
AWAKE - 실시간 주식 공시 정리채널 @darthacking · 65,078 Telegram ranks this channel #47 of 91 here — alongside 90 others — read 2 September 2026
습관이 부자를 만든다. 🧘 @habit4117 · 27,854 Telegram ranks this channel #48 of 87 here — alongside 86 others — read 10 September 2026
선진짱 주식공부방 @sunstudy1234 · 54,428 Telegram ranks this channel #49 of 89 here — alongside 88 others — read 2 September 2026
신영증권 박소연 @sypark_strategy · 29,539 Telegram ranks this channel #54 of 91 here — alongside 90 others — read 8 September 2026
⚡️번개맞은뉴스 - 상위2% 주식텔레그램 채널 @stock_messenger · 25,581 Telegram ranks this channel #58 of 90 here — alongside 89 others — read 14 September 2026
AWAKE - 52주 신고가 모니터링 @awake_realtimeCheck · 22,586 Telegram ranks this channel #63 of 92 here — alongside 91 others — read 20 September 2026
시황맨의 주식이야기 @shmstory · 38,160 Telegram ranks this channel #65 of 89 here — alongside 88 others — read 2 September 2026
This channel appears in 37 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“제약/바이오/미용 원리버 Oneriver” (@pharmbiohana), 29,843 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/pharmbiohana.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.