FDAzilla 483 Deal for Zymergi readers

disclosure: FDAzilla uses Zymergi software.

We love promoting our associates, partners and customers (at least the ones who want to be promoted).

FDAzilla is a website that gathers intelligence on the FDA. They used our software to create the world's largest 483 store. The 483 themselves are redacted PDF files that list the inspectional observations:

If you have time, it's cheaper to go straight to the FDA and get these 483 PDF files. It'll take several weeks and you don't have any idea of the cost until the FOIA job is completed.

But if you value your time, your anonymity and your budget, here's why you go with their store:

• You can buy 483 inspectional observations instantly (otherwise, fill out an FOIA request and wait for an FDA rep to get back to you).

• You can buy the 483 reports anonymously (...other than the NSA knowing, of course).

• Every 483 is $119 a piece.

The FDAzilla Store and InspectorRank tool is especially good when an FDA inspector arrives onsite and you need quick access to the inspectional observations of this specific auditor.

Here's Megan Haggerty's 483 reports. And here's good ole Lance De Souza's 483 reports.

There's plenty of intel on these inspectors; but that also means you need to buy quite a few to get a good idea of the type of FDA inspector you have sitting in the conference room.

So for Zymergi blog readers, FDAzilla is offering the following discount code:

zymergi5

Use this zymergi5 discount code when you buy 5 or more 483 pdf documents and you'll get 16% off!

Keep Up on Contamination Control and Cell Culture Commentary

What does a Korean biologics contract, a Bay-Area biofuels maker, UC Irvine and Chicago-based big-pharma have in common?




None of them use Google+ to keep up to date with the leaders of bioreactor contamination control... (i.e. Zymergi).

...or if Google+ isn't your thing, we update the Zymergi LLC LinkedIn page regularly.

10 Ways to Tell If You Suck at Cell Culture Support

Here are 10 ways to tell if your support of large-scale cell culture, well, sucks:

1. Key performance indicators.
   You don't know what the right KPIs are for cell culture, but you're 100% certain that it's titer.
2. Proven Acceptable Limits.
   You don't have any defined for your critical process parameters and you failed to demand them of Process Development.
3. Control charts. You're not using them or you don't know how to make them, and your bar graphs are just fine, thankyouverymuch. They're not just fine and it's because you can't identify:
4. Special cause vs. common cause variability.
   You investigate common cause variability because that titer seemed too low or too high.
5. C_pK. You don't know what process capability is and you're not calculating them.
6. Histograms. You aren't looking at the distribution of your KPIs.
7. Bi-variate Analysis.
   Linear-regressions, ANOVA, Tukey-Kramer.  You have no idea what this stuff is, 我還不如寫中文.
8. Multivariate Analysis.
   You're not doing these and when you do, Y-responses are treated as X-factors.
9. Local Lab. You don't have a local MSAT lab to run satellite experiments to confirm the hypothesis generated from the plant.
   
   A lot of people assume that you can use the resources of a distant process development lab; but then again, a lot of people like blood sausage.
10. Excel. You're still using Excel to store data. You're still using Excel to analyze data. If you're looking to play varsity cell culture support, you really need to be using a cell culture data management system.

by Oliver Yu

See also:

• MSAT plant support: local data
• Campaign monitoring v. Process Improvement
• MSAT consulting

It's True: FDA Inspectors Judge Books by Covers

It's 483 month over at FDAzilla.com and strategy #5 for avoiding dreaded inspectional observations is:

Don't Neglect Your Physical Plant

While it seems like a no-brainer to maintain the physical plant (i.e. perform work orders and change orders to keep the facility performing), judging the physical plant by appearance is a bit superficial.

FDAzilla writes:

One former compliance official used a simple test to get a sense of how seriously companies took having a clean operation: he’d walk into the men’s room and check it out. “If it isn’t clean in there, how can you be making a good product?” the official says.

Does a dirty men's room mean that an entire facility - whose validated environmental monitoring, bioburden levels do not exceed alert or action limits - is also not clean?  It's one thing to conclude that the factory is out of control by looking at the data within validated systems; it's quite another to be judging from the bathrooms.

Sadly our experience comports with FDAzilla's reporting: that FDA inspectors judge books by their covers.

As the saying goes, "neatness counts," and neatness in the GMP world can help sweep a lot of real GMP problems under the rug.

I know of a plant that would go and paint the handrails in the stairwells every time a contingent of regulatory inspectors arrive.  Handrails that get scratched by the button on the gowns operators wear are scratched up all year long, but as soon as an FDA inspector arrives, you have people out there painting it.

This isn't new to me.  Cornell University would have all kinds of construction: orange nets, backhoes, jackhammer noises all year long, but as soon as it was commencement week and the alumni and parents showed up, all the equipment would get packed up and it'd look just like their college brochure.

Biologics manufacturer knows that neatness counts; and they attend to superficial details because neatness can help them avoid 483 inspectional observations.

Putting Contamination TimeWindow to Use

by Oliver Yu

In a previous post, I introduced the calculation to estimate the earliest time of bioreactor contamination.

And the reason anyone'd ever bother running this calculation is to help direct the focus of contamination investigation.

Have a look at the example from the previous post. The sterility samples collected showed that the 12,000-liter bioreactor was "clean" all the way through 84-hours. By the time 108-hours culture duration rolled around, the dO2 and pH had crashed, prompting us to send the bottles to QC Micro. QC Micro reports that then 96-hour sample was also "hot."

There are folks who'd look at this data and say,

If we were clean at 84-hours, but hot at 96-hours, then bioreactor manipulations in that time-frame (84 to 96) are culprits for contamination.

But what if there were no bioreactor manipulations in that time frame but a sterile envelope manipulation at 77-hours?

Saying the 84-hour sample was "clean" is actually a mistake. It is more accurate to say, "Bioburden levels of the 84-hour sample were less than detectable." And using a clean 84-hour sample to vindicate prior manipulations would be a mistake by disqualifying true root causes.

On the other side of the spectrum are folks who say:

We need to look at every single sterile-envelope manipulation of the bioreactor starting from the time of inoculation at 0-hours.

This ocean-boiling approach is expensive and includes improbable root causes that ought to be disqualified.

The most effective approach lies somewhere in between and - we think - is to estimate the growth rate of the microbe by assuming the last "clean" sample was simply less-than-detectable. And computing this growth rate.

Using this growth rate to estimate the earliest 1 CFU could have penetrated sterile barriers is one scientifically defensible way of balancing the last-clean vs. boil-the-oceans approaches.

As for the assumptions of this method, they are:

• Constant growth rate of microbe. This method assumes that microbes entered the bioreactor in the growth phase and didn't stop. Since microbes (like spore-formers) can be in the stationary phase, the constant growth assumption tends to not include as much time as perhaps should be.
• 1 CFU inoculated the bioreactor. While it is unlikely that a bioreactor breach let in a single CFU or that the SIP killed all organisms except one, assuming 1 CFU tends to include more time and helps counter the assumption of constant growth.
• Once sample pulled, growth stopped. If the organism is an aerobe, this is a good assumption. If not, use the time of QC Micro count for (t).

Bioreactor contamination response is a lot like crime-scene response and investigation, and the contamination time-window calculation is a lot like estimating the time of death (of a murder victim). This information can be used to help rank probable cause and ultimately the most probable cause (i.e. identify the killer).

Get "Time of Contamination" Spreadsheet

Cell Culture Contamination Consultants

This is how we see customers who hire us to fix bioreactor contaminations:


No one likes getting contaminations.

No one wants to search the internet for "bioreactor contamination".

No one wants to pay consultants to help fix them.

But here you are...

...you found us because we write about bioreactor sterility concepts, principles and best-practices.

Sign a confidentiality agreement and give us a call.

Rebuttal to Atmospheric Breaks on Drains

Here's some feedback from an industry colleague regarding air-breaks on drains:

For one thing, BSL-2+ areas like [highly toxic] bacterial fermentation suites require the facility to have closed piping to avoid or minimize aerosol effects and biohazard contamination of people and the environment around the fermentor.  The BMBL 5th Edition (basically the biosafety bible) requires it for BSL-2 and above organisms.

Clearly we know that protecting workers is clearly paramount to safety.  But we also know that not every process uses "BSL-2 and above organisms."  A lot of facilities are designed "just in case" the expression system produces biohazard.

Closed-pipe drain headers requires a deep understanding of SIP cycle design and implementing a robust recipe to get rid of vacuum.

So in closing:

When Was the Bioreactor Actually Contaminated?

by Oliver Yu

In a previous post, I glossed over detection of microbial contamination. I'm certainly no QC Micro expert, but a former co-worker, Mary Jane McRoberts, who was telling me the sensitivity of these QC Micro tests:

me: Hey MJ, what are the chances that there's a bug in the sample, but that your tests just happen to not catch it?

MJ: I tell you what.... if there's one CFU (colony forming unit) in there, my test is going to pick it up.

So suppose the final sample I hand over has exactly 1 CFU in the entire sample.

If you are using 40mL bottles to collect samples, that's a concentration of 1 CFU/40mL = 0.025 CFU/mL.

In a 12,000-liter bioreactor... a.k.a 12,000,000-mL bioreactor, you're looking at 300,000 colony forming units floating around in your production culture before your QC methods are sensitive enough to pick it up.

Knowing this 0.025 CFU/mL is crucial in estimating the contamination time-window.

Contamination TimeWindow

Anytime you have a bioreactor contamination, one (good) question that gets asked is: "So when did the contamination happen?"

This is because the signs of bioreactor contamination show up long after the insult as it takes time for the microbial contaminants to consume detectable amounts of oxygen and nutrients to crash the dO2 and pH signals.

All you need to compute this time-window is a spreadsheet of your contamination timeline:
And the equation for exponential growth:

X = X₀ e^{μ(t - t₀)}

where:

• X is the concentration at time t
• X₀ is the concentration at time t₀
• e is the natural log constant
• μ is the growth rate

If we want to know the time of microbial contamination, we're interested in solving for t₀.

X is given to us by QC Micro...in this example, QC Micro counted the last sample and found the concentration to be:

X = 2.2 x 10⁵CFU/mL

The time of contamination is known to us:

t = 4.5 days

And if we want to be uber-conservative, we assume that the initial insult was simply 1 CFU. So if our bioreactor is 12,000-liters, the initial concentration is 1 CFU/12,000,000mL or:

X₀= 8.3 x 10^-8CFU/mL

We know X, we know t, we know e, but we don't know μ, so at this point we have 1 equation, but 2 unknowns (μ and t₀).

One way to estimate μ is to assume that the "last clean sample" was just short of the detection limit: 0.025 CFU/mL (assuming 40 mL sample bottle).  Solving for the growth rate:

μ = ln ( X/X₀ ) / ( t - t₀ )
μ = ln ( 2.2 x 10⁵/ 0.025 ) / ( 4.5 - 3.5 ) = 16 day^-1

Since we now know the growth rate (μ), we can flip the equation around and solve for the time of the initial insult (t₀):

t₀ = t - ln ( X/X₀ ) / μ
t₀ = 4.5 - ln ( 2.2 x 10⁵/8.3 x 10^-8 ) / 16 = 3.14 days (culture duration)

Using a simple plug 'n chug of the exponential growth equation and plate counts from QC Micro, one can estimate the time at which the microbial contamination actually took place.

Question: What are the implicit assumptions of this method?

See also:

• Microbial contamination probabilities
• Bioreactor Sterility Consulting
• You Suck at SIP

Most Interesting Customers in the World Hire Zymergi

This is generally our experience.

But we're professionals, so we get it.

For prospective customers, this is how it goes:

1. You give us a call and we basically have a phone interview.
   There's actually not much to talk about since we're not yet under confidentiality, so..
2. We need to sign non-disclosure.
   Typically, your Legal department wants us to sign your NDA.  In the meantime, if you need confidentiality you can sign Zymergi's Mutual Confidentiality Agreement.
3. Now, we can chat:
   * You tell us your problems
   * We tell you if we can help and if there's availability.
4. If business sounds worthwhile, you produce a purchase order.
   Vendor on-boarding is typically the rate-limiting step, but Zymergi has seen 36-hour turn arounds.

Next-day onsite service is usually impossible.  But depending on how adept you are at generating a purchase order (PO), we have been able to send consultants the following week.

Get Bioreactor Sterility Consulting

Drain Water vs. Clean Air - Drain Design for Bioreactor Contamination

UPDATE: The point isn't to install air-breaks at all costs.  The point is to use the correct BioSafety Level for your process, recognizing that a lot of facilities are overly-conservative for the processes they run.

On multiple consulting assignments, we are seeing an alarming trend where CIP manifolds and process piping are piped directly to drain.  We have identified direct piping to floor drains as contamination risks.  And our experience mitigating floor drain contamination risk is to cut the piping.

The main objection to this recommendation is that it would compromise the Class 100,000 clean room status of the process space.

With the cut in the piping, the worry is that contaminants from the drain are now able to enter the processing suite and will send your viable airborne particles beyond your environmental monitoring action limits.

But of the unfavorable options available, there's one that's obvious to us.

Your choices are as follows:

• Keep the bioreactor sipping drain water, but hey, you've got a Class 100,000 processing suite.
• Cut the pipes and get your bioreactor sipping fresh, 20 air-changes-per-hour filtered air.

It turns out that that we aren't the only ones who think this is true.  In a 2006 article on biocontamination control, @GENBio reported the "original views" of chemical engineer, Jim Agalloco:

...Trying too hard to protect the bioreactor environment can adversely affect the ability to sterilize equipment. For example, a steam sterilizer normally requires an atmospheric break between its drain and the facility drain, but some biotech companies object to that layout because it compromises the controlled environment.

Somehow, the viable airborne particles of the environment matter more than the ability to sterilize equipment.  They further state:

Eliminating the atmospheric break introduces more piping and surfaces, which leads to more opportunities for microbes to grow. To protect the outside of the tank, they purposely risk contaminating the inside.

Which is exactly our position on the matter.

We're aware that managing perceived action is as important as managing action.  But taking the action that keeps cell cultures from contamination is always defensible even if it flies in the face of perception.

Zymergi Bioreactor Sterility Consulting

Cancer Becoming Resistant to Cancer Drugs

The Massachusetts Institute of Technology discovered one way in which a certain class of cancers is becoming resistant to cancer drugs.

Cancer drugs known as ErbB inhibitors have shown great success in treating many patients with lung, breast, colon and other types of cancer. However, ErbB drug resistance means that many other patients do not respond, and even among those who do, tumors commonly come back.

To be honest, I had to look up ErbB inhibitor as I hadn't heard of that term.  It turns out I knew them as epidermal growth factor receptors (EGFRs).

Epidermal growth factor receptors are proteins that live on the cell membrane.  It's normal for cells in your body to have them.  When bound to the ligand, it triggers the cellular machinery to migrate, adhere and proliferate... all the things we don't want cancer cells to do.

There are certain types of cancer that are characterized by over-expression of ErbB and therefore companies have developed drugs that target ErbB in order to inhibit them... thus the term ErbB inhibitor.

What MIT is saying is that some tumors are developing resistance to these types of drugs.  And they found this with a database exercise.  They queried some wonkish database and found drug-resistance when ErbB receptors are found with AXL receptors across across many types of cancer, including lung, breast and pancreatic.

The MIT conclusion is to target the AXL receptors alone or in combination to attack tumors that are becoming resistant to commercial ErbB inhibitors.

Commercialized ErbB inhibitors include:

• Amgen's Vectibix (panitumumab) (ErbB-1)
• Bristol Myer Squibb + Eli Lilly Erbitux (cetuximab)
• AstraZeneca's Iressa (gefitinib)
• Genentech/Roche's Tarceva (erlotinib)
• Genentech/Roche's Herceptin (trastuzumab) (ErbB-2)
• Genentech/Roche's Perjeta (pertuzumab)

My guess is that we're going to see companies targeting this AXL receptor and in a few years, see cell culture processes designed to make biologics that inhibit AXL.

FDA's Metadata is Public. FOIA through 3rd-Parties.

A month ago, former-NSA-employee turned whistleblower: Ed Snowden, revealed far-reaching surveillance capabilities of the National Security Agency, specifically: metadata collection.

What is Metadata?

Metadata refers to data about the data.

Sort of weird to refer to something that way, but here's a simple example:


In fact, our OSI PI historian search engine: ZOOMS stands for Zymergi Object-Oriented Metadata Search.

• The data itself is time-series data.  
• The metadata is all the information that describes it:
  "V7410 pH" is metadata that our search engine archives.

What the US federal courts are saying is that the data (content of phone calls, content of emails) is protected by the 4th Amendment; but that the metadata (sender, receiver, time of call, duration of call, etc.) is not and therefore available for archival by the NSA for "fighting terrorists."

What does this have to do with biotech manufacturing?

Well, our market is regulated by a federal agency called the FDA, and when you contact them up to request information (called an FOIA request "Freedom of Information Act"), they don't just serve up the documents, charge you and be on your respective ways:

Your FOIA request is logged in a database and your FOIA request can be requested like any other FDA document.

This means:

Your business dealings as they pertain to the FDA are as public as your personal life is to the NSA.

• If you think Amgen wants to buy Onyx but you don't have access to insider information?  Send an FOIA to the FDA asking for all recent documents requested by Amgen.  If Amgen is doing due diligence on the deal, they may leave a trail there.
• If you thought Allergan was going to buy MAP Pharmaceuticals and wanted to test your hypothesis, send an FOIA to request the Allergan metadata.

If you're requesting actual documents, the data will be redacted; however, the log of the requests (the metadata) is public and available in sans redaction.

This is why our customer, FDAzilla, built the world's largest 483 store.  When you buy 483s from FDAzilla, you get the product without having to give up who you are and therefore business information you'd rather not have shared.

And if you're interested in more than just 483s, they have a compliance monitoring service that's built to suit your needs.

by Oliver Yu

Once you purchase through FDAzilla, it is true that they now have a record of your information; but the difference is that they are not compelled by law to share it to the public as the FDA is through the Freedom of Information Act.

On top of anonymously getting information, you also get it instantly...(which we all know from FDA FOIA experience, isn't necessarily on your timeline).

4 out of 5 Best-Selling Medicines for 2013 are Biologics

by Oliver Yu

According to the business/investing website The Motley Fool, the best selling drugs for 2013 are:

1. Humira (4.8B) - biologic
2. Advair
3. Enbrel (4.1B) - biologic
4. Lantus (3.5B) - biologic
5. Avastin (3.3B) - biologic

The combined sales of the top 5 drugs come in near 20 billion dollars.  With 15.6 billion (79%) from the sales of biologics.

Using 2012 as baseline, Humira, Enbrel and Lantus were on the list of top selling biologics.  But Remicade, Rituxan and Herceptin all placed higher than Avastin.

Which gets me thinking... did the fool.com author work off incomplete data?

• 5 of 8 Top-Selling Drugs for 2012 were biologics
• Top-Selling Drugs for 2011

Veteran FDA Inspector Answers Questions for FDAzilla's 483 Month

by Oliver Yu

Altruistic FDA inspector explains his perspective at this Q&A post:

FDAzilla asks questions of a veteran FDA auditor

What's very interesting is that there is an open admission to the "tremendous amount of [inspector-to-inspector] variability" when queried on level of scrutiny as well as US vs. ex-US inspections.

How is a federal agency supposed to enforce a uniform code with "tremendous variability"?

My grapevine tells me that the same manufacturing plant... running with essentially the same management, the same people, and the same underlying issues will face different scrutiny just because their plant got sold to another company.

It's just strange that someone can think how "tremendous variability" in inspections and auditing comports with an "agency [who is] mission-driven to stop adulterated product from distribution."

Read the original story here.

Every MSAT's Response to Process Development

Reducing variability is the only thing the Manufacturing team can control.  Ways to do this involve getting more accurate probes, improving control algorithms, upgrading procedures, etc.

But there are limits. Probes are only so precise. Transmitter may discretize the signal and add error to the measurement. The cell culture may have intrinsic variability.

What makes for releasable lots are cell cultures executed within process specifications.  And measuring a process parameter's variability in relation to the process specification is the SPC metric: capability.



Process specifications are created by Process Development (PD). And at the lab-scale, it's their job to run DOE and explore the process space and select process specifications narrow enough to produce the right product, but wide enough that any facility can manufacture it.

by Oliver Yu

It's tempting to select the ranges that produce the highest culture volumetric productivity.  But that would be a mistake if those specifications were too narrow relative to the process variability.  You may get 100% more productivity, but at large-scale be only able to hit those specifications 50% of the time resulting in a net 0% improvement.

The key is to pick specification limits (USL and LSL) that are wide so that the large-scale process is easy to execute.  And at large-scale, let the MSAT guys find the sweet-spot.