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[159.112.244.35]) by mx.google.com with UTF8SMTPS id af79cd13be357-8d00e5bc36asi277441885a.491.2026.03.26.05.49.53 for (version=TLS1_2 cipher=ECDHE-ECDSA-AES128-GCM-SHA256 bits=128/128); Thu, 26 Mar 2026 05:49:54 -0700 (PDT) Received-SPF: pass (google.com: domain of bounce+91e48a.63af5d-tjphuhs=gmail.com@mg-d0.substack.com designates 159.112.244.35 as permitted sender) client-ip=159.112.244.35; Authentication-Results: mx.google.com; dkim=pass header.i=@mg-d0.substack.com header.s=mailo header.b=SKUUcDRh; dkim=pass header.i=@mailgun.org header.s=mg header.b=HRTU+Ehp; spf=pass (google.com: domain of bounce+91e48a.63af5d-tjphuhs=gmail.com@mg-d0.substack.com designates 159.112.244.35 as permitted sender) smtp.mailfrom="bounce+91e48a.63af5d-tjphuhs=gmail.com@mg-d0.substack.com"; dmarc=pass (p=REJECT sp=REJECT dis=NONE) header.from=substack.com DKIM-Signature: a=rsa-sha256; v=1; c=relaxed/relaxed; d=mg-d0.substack.com; q=dns/txt; s=mailo; t=1774529393; x=1774536593; h=List-Unsubscribe-Post: List-Unsubscribe: List-Post: List-Id: List-Archive: List-Owner: Reply-To: In-Reply-To: References: Sender: Sender: Date: Message-Id: To: To: From: From: Subject: Subject: Content-Type: Mime-Version: X-Feedback-Id; bh=AVLpsflgM9/BtKnz9U62NaHxzuP0Z42Zh7smBw/a/vc=; b=SKUUcDRhWiIX8tRGrbszSFjEaKGpsrP//Lbp1e/u4K4nO5AfwtZzfpDMLzS6xKaLpQEujYY7SfTyxu8k1rQY0vJowPf/H+XshzZSGJN9t0moWuVXbUo5oDwiL5cv2YRCK3zV+GX8sCjxV4xOpwDNXV1d/Q2Z1fqAWWMa0YQsLTw= DKIM-Signature: a=rsa-sha256; v=1; c=relaxed/relaxed; d=mailgun.org; q=dns/txt; s=mg; t=1774529393; x=1774536593; h=List-Unsubscribe-Post: List-Unsubscribe: List-Post: List-Id: List-Archive: List-Owner: Reply-To: In-Reply-To: References: Sender: Sender: Date: Message-Id: To: To: From: From: Subject: Subject: Content-Type: Mime-Version: X-Feedback-Id; bh=AVLpsflgM9/BtKnz9U62NaHxzuP0Z42Zh7smBw/a/vc=; b=HRTU+Ehp6Kc2YSQIwzqWCcEz5ZpYsElkyP3o96JxHBFZDbBrTP4SxyWY/QkHnIh36CIgWu4eHV4J46UUXFxsus5gaFhPE0+cBNv4lueXymH3YhVBmT0QGnItOafoSlWFl3BT6c1zxmqzqVbYOr/mdHUpDfWjUKhq7i+jH1XLkoY= X-Mailgun-Sid: WyJkZWU4NyIsInRqcGh1aHNAZ21haWwuY29tIiwiNjNhZjVkIl0= X-Feedback-Id: postmaster@mg-d0.substack.com:post:6148c7d8a45790427cda307f:mailgun Received: by 8b4645a9cf0a08094a79daf9109fd50bc4ad3ea622c0d4ec4f89f4bec67430ea with HTTP id 69c52b71fc419e8b5adf2dfa; Thu, 26 Mar 2026 12:49:53 GMT X-Mailgun-Sending-Ip: 159.112.244.35 Mime-Version: 1.0 Content-Type: multipart/alternative; boundary="7f8858bfb9cbe8756671738bf97fb2fdf88adf98fd640a170119496833f3" Subject: The Test That's Actually Failing - 3 of 6 Failed Sterility at 99.8% From: Derek from Peptide Price To: tjphuhs@gmail.com X-Mailgun-Tag: post X-Mailgun-Track-Clicks: false Message-Id: <20260326124921.3.cef546f1d4953f68@mg-d0.substack.com> Date: Thu, 26 Mar 2026 12:49:21 +0000 Feedback-Id: post-192201789:cat-post:pub-3365367:substack Sender: Derek from Peptide Price References: In-Reply-To: Reply-To: Derek from Peptide Price List-Owner: List-Url: List-Archive: List-Id: List-Post: List-Unsubscribe: List-Unsubscribe-Post: List-Unsubscribe=One-Click X-Mailgun-Variables: {"category": "post", "email_generated_at": "1774529392576", "is_freemail": "true", "post_audience": "everyone", "post_id": "192201789", "post_type": "newsletter", "pub_community_enabled": "true", "publication_id": "3365367", "subdomain": "derekpruski", "user_id": "273622398"} --7f8858bfb9cbe8756671738bf97fb2fdf88adf98fd640a170119496833f3 Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: quoted-printable View this post on the web at https://derekpruski.substack.com/p/the-test-th= ats-actually-failing-3 Yesterday I ran a poll asking which test you=E2=80=99d add on top of identi= fication, purity, and net content. 127 votes came in: Endotoxins =E2=80=94 55 votes (43%) Sterility =E2=80=94 50 votes (39%) Heavy Metals =E2=80=94 22 votes (17%) Endotoxins won. And honestly, that=E2=80=99s a reasonable choice =E2=80=94 = endotoxins are well understood, they have clear pass/fail thresholds, and t= hey=E2=80=99re directly relevant to safety. But here=E2=80=99s what the real-world data is actually showing: sterility = is the test that=E2=80=99s failing more than anything else across vendors r= ight now. Not at alarming rates. But it=E2=80=99s happening =E2=80=94 and it=E2=80=99= s happening on batches where everything else looks perfect. Peptidology just shared their MOTS-C COA with me (Lot 1670), and it=E2=80= =99s a textbook example of exactly this. Let=E2=80=99s walk through it. Everything else on this batch passed cleanly. Vanguard Laboratory ran a comprehensive panel on 2/26/2026: Chromatographic purity (HPLC-UV/VIS): >99.80% across all three vials tested Assay/net content: 10.36 mg, 10.32 mg, 10.36 mg =E2=80=94 labeled at 10 mg,= so slight overfill, which is normal and good Heavy metals (ICP-MS): chromium, arsenic, cadmium, lead, and mercury all no= n-detect Endotoxins (LAL): both samples passed at <5.00 EU/mg, well under the USP/FD= A threshold Residual solvents (GC-MS): all 16 solvents tested =E2=80=94 benzene, chloro= form, dichloromethane, acetone, ethanol, and more =E2=80=94 all non-detect TFA: non-detect, below 0.10% Solubility: fully soluble in 2 mL water on both samples tested Container closure integrity (dye ingress): both passed On paper, this is as clean as a COA gets. Then you get to sterility. Vanguard ran USP <71> sterility testing on five samples from this lot. Thre= e failed =E2=80=94 growth detected. Two passed =E2=80=94 no growth. Eagle Analytical Services ran an independent ScanRDI sterility test on a se= parate sample from the same lot. That one passed. Six total sterility tests across two independent labs. Three fail, three pa= ss. Same lot. Same batch. This is not a vendor failure. This is sterility testing doing exactly what = it=E2=80=99s supposed to do =E2=80=94 and showing you how complicated this = actually is. Why can samples from the same lot give different sterility results? Sterility isn=E2=80=99t a property of the compound itself. MOTS-C doesn=E2= =80=99t inherently have bacteria in it. What sterility testing is detecting= is contamination =E2=80=94 and contamination is not uniform. Think of it like this: if you dropped a single grain of dirt into a swimmin= g pool, some water samples would test positive and some would test negative= depending on where you pulled from. The contamination exists somewhere, bu= t it=E2=80=99s not evenly distributed. A few mechanisms that explain variable results on the same lot: 1. Environmental contamination during fill/finish The peptide compound itse= lf may be clean. But the process of filling vials and lyophilizing (freeze-= drying) happens in a controlled environment =E2=80=94 and that environment = isn=E2=80=99t always perfect. A brief lapse in cleanroom conditions, a fail= ure of laminar flow, an unsterilized surface =E2=80=94 any of these can int= roduce contamination into some vials but not others. 2. Low-level contamination below detection threshold The contamination load= may be very low =E2=80=94 a small number of organisms. If only a handful o= f bacteria are present, the test may detect it in some samples and miss it = in others depending on exact volume tested and starting organism count. 3. Two different methods were used here The Vanguard results used USP <71> = =E2=80=94 a culture-based method that incubates samples for 14 days to see = if anything grows. Eagle used ScanRDI, which stains and filters the sample = and counts organisms directly under fluorescent light in roughly 24 hours. = These two methods can give different results on borderline samples. Neither= is wrong =E2=80=94 they=E2=80=99re measuring slightly different things wit= h different sensitivities. 4. Sampling variability For a 10 mg vial, the tested portion is a fraction = of total content. If contamination is localized to a specific area of the v= ial, some draws will capture it and others won=E2=80=99t. What does this mean for researchers? A few takeaways: A single sterility pass doesn=E2=80=99t guarantee the entire lot is sterile= =2E This is why testing multiple sample= s and using independent labs matters.=20= Peptidology sent samples to two different labs =E2=80=94 that=E2=80=99s the= right approach. Purity >99% tells you nothing about sterility. These are completely separat= e things. A peptide can be analytically perfect and still have microbial co= ntamination introduced during manufacturing. The argument =E2=80=9Cif purit= y is high, everything else is fine=E2=80=9D doesn=E2=80=99t hold. Sterility failures don=E2=80=99t automatically mean a vendor has bad practi= ces. It means contamination is hard to eliminate entirely and even harder t= o detect consistently. What matters is whether the vendor is testing at all= , how many samples they=E2=80=99re running, and what they do when failures = show up. Endotoxins and sterility are not the same test. Endotoxins (LAL) detect fra= gments from gram-negative bacterial cell walls =E2=80=94 they can be presen= t even if all live organisms are dead or removed. Both tests matter indepen= dently, and both passed on this COA. The bottom line You voted endotoxins as the most important additional test. That=E2=80=99s = not wrong =E2=80=94 endotoxins are important and worth testing for. But if you=E2=80=99re looking at what=E2=80=99s actually coming back with f= ailures on otherwise clean product right now, sterility is making the stron= gest case for itself. Peptidology sharing this data publicly =E2=80=94 including the failures =E2= =80=94 is exactly the kind of transparency the research community should be= pushing vendors for. The uncomfortable results matter more than the clean = ones. All compounds referenced are for research purposes only, not for human cons= umption. Unsubscribe https://substack.com/redirect/2/eyJlIjoiaHR0cHM6Ly9kZXJla3BydXN= raS5zdWJzdGFjay5jb20vYWN0aW9uL2Rpc2FibGVfZW1haWw_dG9rZW49ZXlKMWMyVnlYMmxrSW= pveU56TTJNakl6T1Rnc0luQnZjM1JmYVdRaU9qRTVNakl3TVRjNE9Td2lhV0YwSWpveE56YzBOV= Ek1TXpreUxDSmxlSEFpT2pFNE1EWXdOalV6T1RJc0ltbHpjeUk2SW5CMVlpMHpNelkxTXpZM0lp= d2ljM1ZpSWpvaVpHbHpZV0pzWlY5bGJXRnBiQ0o5LmwwOEd5SzFlZzc5U2VkanRReU4tNGZfN2J= TVHBQZVZaU2RacDhJOFptZUkiLCJwIjoxOTIyMDE3ODksInMiOjMzNjUzNjcsImYiOnRydWUsIn= UiOjI3MzYyMjM5OCwiaWF0IjoxNzc0NTI5MzkyLCJleHAiOjIwOTAxMDUzOTIsImlzcyI6InB1Y= i0wIiwic3ViIjoibGluay1yZWRpcmVjdCJ9.8d-POwTh0Idp8vS7ChMrQ0uw0lUinURU24N928i= gUE0? --7f8858bfb9cbe8756671738bf97fb2fdf88adf98fd640a170119496833f3 Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: quoted-printable The Test That's Actually= Failing - 3 of 6 Failed Sterility at 99.8%3D""
Yesterday I ran a poll asking which test you’d add on top of = identification, purity, and net content.
͏     ­T= 7;     ­͏     ­͏     &= #173;͏     ­͏     ­͏   =   ­͏     ­͏     ­͏= ;     ­͏     ­͏     &#= 173;͏     ­͏     ­͏   &= #8199; ­͏     ­͏     ­͏=     ­͏     ­͏     = 73;͏     ­͏     ­͏   &#= 8199; ­͏     ­͏     ­͏ =     ­͏     ­͏     = 3;͏     ­͏     ­͏   = 199; ­͏     ­͏     ­͏ &= nbsp;   ­͏     ­͏     ­= ;͏     ­͏     ­͏   Q= 99; ­͏     ­͏     ­͏ &n= bsp;   ­͏     ­͏     ­= ͏     ­͏     ­͏   ̳= 9; ­͏     ­͏     ­͏ &nb= sp;   ­͏     ­͏     ­&= #847;     ­͏     ­͏    = ; ­͏     ­͏     ­͏ &nbs= p;   ­͏     ­͏     ­&#= 847;     ­͏     ­͏    = ­͏     ­͏     ­͏  = ;   ­͏     ­͏     ­= 47;     ­͏     ­͏     = ­͏     ­͏     ­͏  =   ­͏     ­͏     ­T= 7;     ­͏     ­͏     &= #173;͏     ­͏     ­͏   =   ­͏     ­͏     ­͏= ;     ­͏     ­͏     &#= 173;͏     ­͏     ­͏   &= #8199; ­͏     ­͏     ­͏=     ­͏     ­͏     = 73;͏     ­͏     ­͏   &#= 8199; ­͏     ­͏     ­͏ =     ­͏     ­͏     = 3;͏     ­͏     ­͏   = 199; ­͏     ­͏     ­͏ &= nbsp;   ­͏     ­͏     ­= ;͏     ­͏     ­͏   Q= 99; ­͏     ­͏     ­͏ &n= bsp;   ­͏     ­͏     ­= ͏     ­͏     ­͏   ̳= 9; ­͏     ­͏     ­͏ &nb= sp;   ­͏     ­͏     ­&= #847;     ­͏     ­͏    = ; ­͏     ­͏     ­͏ &nbs= p;   ­͏     ­͏     ­&#= 847;     ­͏     ­͏    = ­͏     ­͏     ­͏  = ;   ­͏     ­͏     ­= 47;     ­͏     ­͏     = ­͏     ­͏     ­͏  =   ­͏     ­͏     ­T= 7;     ­͏     ­͏     &= #173;͏     ­͏     ­͏   =   ­͏     ­͏     ­͏= ;     ­͏     ­͏     &#= 173;͏     ­͏     ­͏   &= #8199; ­͏     ­͏     ­͏=     ­͏     ­͏     = 73;͏     ­͏     ­͏   &#= 8199; ­͏     ­͏     ­͏ =     ­͏     ­͏     = 3;͏     ­͏     ­͏   = 199; ­͏     ­͏     ­͏ &= nbsp;   ­͏     ­͏     ­= ;͏     ­͏     ­͏   Q= 99; ­͏     ­͏     ­͏ &n= bsp;   ­͏     ­͏     ­= ͏     ­͏     ­͏   ̳= 9; ­͏     ­͏     ­͏ &nb= sp;   ­
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The Test That's Actually Failing - 3 of 6 Failed Sterility at 99.8%<= /h1>
<= table role=3D"presentation" width=3D"auto" border=3D"0" cellspacing=3D"0" c= ellpadding=3D"0">
Derek

<= /table>
 
3D""
<= /td>
3D""
3D""
3D""
=
 

Yesterday I ran a poll asking which test you’d ad= d on top of identification, purity, and net content.

127 votes came in:

  • Endotoxins — 55 votes (43%)=

  • Sterility —= ; 50 votes (39%)

  • = Heavy Metals — 22 votes (17%)

Endotoxins wo= n. And honestly, that’s a reasonable choice — endotoxins are we= ll understood, they have clear pass/fail thresholds, and they’re dire= ctly relevant to safety.

But here’s what the re= al-world data is actually showing: sterility is the test tha= t’s failing more than anything else across vendors right now.

Not at alarming rates. But it’s happening — a= nd it’s happening on batches where everything else looks perfect.

=

Peptidology just shared their MOTS-C COA with me (Lot 1670), a= nd it’s a textbook example of exactly this. Let’s walk through = it.

<= /div>

Everything else on this batch passed cleanly.

Vanguard Laboratory ran a comprehensive panel on 2/26= /2026:

  • Chromatographic purity (HPLC-UV/VIS): >99.80% a= cross all three vials tested

  • Assay/net content: 10.36 mg, 10.32 mg, 10.36 mg — labeled= at 10 mg, so slight overfill, which is normal and good

  • Heavy metals (ICP-MS): chromium, a= rsenic, cadmium, lead, and mercury all non-detect

  • Endotoxins (LAL): both samples passed at &= lt;5.00 EU/mg, well under the USP/FDA threshold

  • Residual solvents (GC-MS): all 16 solvents t= ested — benzene, chloroform, dichloromethane, acetone, ethanol, and m= ore — all non-detect

  • TFA: non-detect, below 0.10%

  • Solubility: fully soluble in 2 mL water on both sampl= es tested

  • Contain= er closure integrity (dye ingress): both passed

O= n paper, this is as clean as a COA gets.

3D"image.png"<= /a>
3D"image.png"
3D"image.png"

Then you get to sterility.

Vanguard ran USP <71> sterility testing on five samples fr= om this lot. Three failed — growth detected. Two passed — no gr= owth.

Eagle Analytical Services ran an independent ScanRDI = sterility test on a separate sample from the same lot. That one passed.

=

Six total sterility tests across two independent labs. <= /span>Three fail, three pass. Same lot. Same batch.

This is not a vendor failure. This is sterility testing doing exa= ctly what it’s supposed to do — and showing you how complicated= this actually is.

Why can samples from the same lot = give different sterility results?

Sterility isn= 217;t a property of the compound itself. MOTS-C doesn’t inherently ha= ve bacteria in it. What sterility testing is detecting is contamination = 212; and contamination is not uniform.

Think of it like thi= s: if you dropped a single grain of dirt into a swimming pool, some water s= amples would test positive and some would test negative depending on where = you pulled from. The contamination exists somewhere, but it’s not eve= nly distributed.

A few mechanisms that explain variable res= ults on the same lot:

1. Environmental contaminatio= n during fill/finish The peptide compound itself may be clea= n. But the process of filling vials and lyophilizing (freeze-drying) happen= s in a controlled environment — and that environment isn’t alwa= ys perfect. A brief lapse in cleanroom conditions, a failure of laminar flo= w, an unsterilized surface — any of these can introduce contamination= into some vials but not others.

2. Low-leve= l contamination below detection threshold The contamination = load may be very low — a small number of organisms. If only a handful= of bacteria are present, the test may detect it in some samples and miss i= t in others depending on exact volume tested and starting organism count.

3. Two different methods were used here The Vanguard results used USP <71> — a culture-based = method that incubates samples for 14 days to see if anything grows. Eagle u= sed ScanRDI, which stains and filters the sample and counts organisms direc= tly under fluorescent light in roughly 24 hours. These two methods can give= different results on borderline samples. Neither is wrong — theyR= 17;re measuring slightly different things with different sensitivities.

4. Sampling variability For a 10= mg vial, the tested portion is a fraction of total content. If contaminati= on is localized to a specific area of the vial, some draws will capture it = and others won’t.

What does this mean fo= r researchers?

A few takeaways:

A = single sterility pass doesn’t guarantee the entire lot is sterile. Th= is is why testing multiple samples and using independent labs matters. Pept= idology sent samples to two different labs — that’s the right a= pproach.

Purity >99% tells you nothing about sterility. = These are completely separate things. A peptide can be analytically perfect= and still have microbial contamination introduced during manufacturing. Th= e argument “if purity is high, everything else is fine” doesn&#= 8217;t hold.

Sterility failures don’t automatically m= ean a vendor has bad practices. It means contamination is hard to eliminate= entirely and even harder to detect consistently. What matters is whether t= he vendor is testing at all, how many samples they’re running, and wh= at they do when failures show up.

Endotoxins and sterility = are not the same test. Endotoxins (LAL) detect fragments from gram-negative= bacterial cell walls — they can be present even if all live organism= s are dead or removed. Both tests matter independently, and both passed on = this COA.

The bottom line

Yo= u voted endotoxins as the most important additional test. That’s not = wrong — endotoxins are important and worth testing for.

But if you’re looking at what’s actually coming back with = failures on otherwise clean product right now, sterility is making the stro= ngest case for itself.

Peptidology sharing this data public= ly — including the failures — is exactly the kind of transparen= cy the research community should be pushing vendors for. The uncomfortable = results matter more than the clean ones.

All compounds re= ferenced are for research purposes only, not for human consumption.

Upgrade to paid

You're currently a free = subscriber to Peptide Price. For the full experience, upgrade your subscription.<= /span>

Upgrade to paid

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