Controllable Parameters of Mammalian Cell Culture

Einstein famously said:

Insanity [is] doing the same thing over and over again and expecting different results.

Which got me thinking...

Question: Is there such a thing as doing the same thing over and over again and getting different results?

Answer: Biotech Manufacturing

Rob Caren once asked: "How hard can (large-scale) cell culture be? It's ONE unit operation."

He also observed that large-scale chromatography shouldn't be that hard either:

• Send the pool through that fixed-bed reactor.
• When the optical density is not zero shut this valve and open that valve.
• Try not to send product to drain.

On both counts, he's right, but I can only speak to the cell culture side.

When running bioreactors, there are a few parameters that are within your control. These parameters are sometimes called "knobs" because the production team can literally go to the control system and "turn a knob" (or click a few buttons on the SCADA) to change the parameter.

For the bioreactor or fermentor, those knobs are:

pH. The intracellular pH is known to change the activity of enzymes that run the rates of metabolic reactions. Since cells regulate intracellular pH, the best you can do is to control the extracellular pH. In reality, the pH for the process is specified. And if specified well, the specification will come with a target range and a proven acceptable range. At commercial scale, you ought to be able to operate within the proven acceptable range. For more information on pH control in mammalian cultures, see this.

Dissolved oxygen. Maximizing cellular productivity means aerobic metabolism. From university biochemistry, we know that anaerobic metabolism produces far less energy (2 ATP) than aerobic metabolism (38 ATP). We also know from chemistry that the solubility of oxygen in water is quite low (<10 mg/L when temperature > 15 degC). Therefore, it is important that the bioreactor supplies oxygen. Some bioreactors supply air and others supplement with oxygen. While the dissolved oxygen range is typically specified by the process, the air supply, air/oxygen mix, flow rates and sparge-type can be determined by the facility. As previously discussed, dissolved oxygen depends on other parameters such as agitation and temperature and can be changed within the specified range.

Temperature. Temperature control happens with the bioreactor jacket where water is flowed around the outside surface of the bioreactor. When the temperature gets too hot, the control system sends cooler water; and when the temperature of the culture gets too cold, the control system sends hotter water. While temperature is typically specified, there are processes that will intentionally cool the culture to reduce the rate of metabolic reactions and extend culture viability. Also, since temperature is defined in a range, the setpoint is a turnable knob.

Agitation. Agitation is typically not specified by the process, just that the cells must be suspended (i.e. not settled on the bottom of the bioreactor).  In practice agitation rate is determined by power-to-volume calculations and stays constant for the bioreactor, nonetheless, this is a manipulatable parameter when running bioreactors.

Timing of Inoculation. Inoculation density is often specified by the process. But there's no way to "dial down" or "dial up" inoc density in a control system somewhere like you can with pH, dissolved oxygen, temperature and agitation. When cells grow, the cell density naturally increases, so the way to control inoculation density is to time it (i.e. wait vs. not wait).

Timing of feeds. In fed-batch cultures, additional nutrients are added to the culture. The additional nutrients tend to increase the osmolality and the additional volume can help dilute the cellular waste (like ammonium). Not in all processes, but in some processes, the timing of feeds have been shown to impact culture productivity.

Timing of shifts. Some processes are specified with changes in setpoints of the aforementioned parameters (e.g. pH or Temperature). The shift specifications come in the form of: "When the culture duration reaches X hours" or "when the cell density reaches Y x 10⁶," then change the set point up/down.

When building multivariate models, it is crucial that controllable parameters are modeled as factors and here's why:

When your model shows can correlate significant main effects and interactions to some process output (e.g. titer or quality attribute), you can actually step out of theory and prove it in practice.

ZOOMS 2 - Fastest Way to View Trends

So in addition to biologics manufacturing commentary, it turns out that Zymergi is actually a for-profit business that provides software, consulting and technical support.

For 2014, we're pretty much booked on the technical support side, but I wanted to take some time to talk about our software products.

Our flagship product is ZOOMS, which is an acronym for Zymergi Object-Oriented Metadata Search.  And in 2014 - thanks to Edward Snowden, more people know what metadata is than in 2008 when we started ZOOMS (v1.0)

So why are we interested in searching metadata? Well, let's take a step back. When working the front lines of campaign monitoring and process support, we noticed that viewing trend data (i.e. tag values plotted against time) was the principal component of process understanding. The more trends a person reviewed, the more process knowledge they gained and the more they understood normal from abnormal.

And in all that time, very few people actually learn to speak "Automationese."

"Hey, did you see that weird thing going on with T100.GLOBAL.CLX.AI05.PV?"
- No one ever

In the automation world, everything is a tag. In the Manufacturing Sciences world, everything is about a measurable parameter within the process. So when you listen to the process scientists and engineers talk, it's always about some parameter (e.g. "Optical Density") in some unit (e.g. "Tank 100"). That right there is the metadata of a tag.

The tag takes care of the Y-axis on the trend. What about the X-axis?

The X-axis deals with time-windows: start times and end times and the metadata around the time-windows are called, "batches." Specifically using S88 terminology, people involved with campaign support are interested in Unit Procedures, a.k.a. "unitbatches."

I'll leave the formal definition of "unit procedure" up to the automation gurus, but to a Manufacturing Sciences data engineer, a unit procedure is a process that happens on a piece of process equipment.

So say you're making rituximab in production bioreactor T100 using the version 1.1 process and batch R2D201 ran from 20-Dec-2013 to 28-Dec-2013... that there is a unit procedure:

batchid	unit	product	procedure	start time	end time
R2D201	T100	rituximab	production culture version 1.1	20-Dec-13	28-Dec-13

The metadata around this time-window (i.e 12/20/2013 to 12/28/2013) are as follows:

• R2D201
• T100
• rituximab
• production culture version 1.1

So it stands to reason that if an internet user who knows nothing about a subject can type keywords into Google and get the most relevant results on that subject; that in 2014, a process citizen who doesn't know too much about the process ought to be able to type some keywords into a webpage and get some process trends.

And now they can: Introducing ZOOMS 2:



Learn More

Post-Licensure Cell Culture Process Improvements

There's a great article out in GEN on cell culture process improvement, in particular, the Dr. Yuval Shimoni segment on the "low hanging fruits" of post-licensure improvements.

From the article:

At the CHI conference, Dr. Shimoni demonstrated how changes to cell culture media can make a difference by increasing production capacity through greater cellular productivity.

As I didn't go to the conference, I am left thinking that his feat was pretty impressive.  Changing media components post-licensure is quite daring.

The biologics license agreement (BLA) will call out the exact ingredients +/- percentages on each media component.  And changing a single component can (and has shown to) alter product quality.

Changing several media components, if in fact, that's what he did, is quite the feat and would take testicular fortitude of magnitude 10 on the Moh's scale: Any adverse impact on product quality - no matter the cell productivity improvements - is unwelcome.

Pulling off a media-change post-licensure is not only a technical accomplishment, but a political one as well.  

Unnecessary Testing in cGMP World

by Oliver Yu

In the world of soaring medical costs, we have unnecessary medical tests and procedures sapping precious healthcare dollars.

The thing about these medical tests is that they are necessary for someone under some circumstances, just not for most people under most circumstances.

So is the case in the world of GMP biologics manufacturing. There are

Image courtesy of the Chemical Heritage Foundation Collections.

plenty of tests that need to happen to produce a releasable lot. There are in-process tests; there of Certificate of Analysis (CofA) tests.  There are analytical tests you for engineering runs; there are tests you perform on contaminated lots, but not others.

But regardless of what test you are performing, the litmus test for performing the test or analysis is:

Does the result of the test help me make a decision?

Consider the following snippet from a computer program:

   if ( testResult == PASS )
   {
      forwardProcessBatch();
   }
   else
   {
      forwardProcessBatch();
   }

In this case, if I run a test and pass, I get to forward process the batch. If the test fails, I still get to forward process the batch. So if in either case, I get to forward process the batch, why should I bother doing the test? The result of the test does not do anything to serve the outcome!

Another good way to approach the question of whether or not to perform a test is to see if you can write down a plan for what to do with the test result. If you can write down a reasonable plan and stick with the plan prior to getting the test results, then there's a good reason to perform the test; otherwise, you're simply on a fishing expedition and making it up as you go along.

FIO Samples

There exists "For Information Only" samples that are specified into the process.  For example, concentrations of ammonium (NH₄⁺), sodium (Na⁺), pO₂ and pCO₂ are measures of cell culture metabolism that are useful for long-term process understanding.  They likely never be used to make a forward-process decision, though they can be used for retrospective justification of discrepancies or as variables during multivariate data analysis.

In my experience, these routine FIO samples are contentious.  On one hand, they serve the purpose of long-term, large-scale process understanding as well as sporadic justification for discrepancies.  On the other hand, if FIO samples get used enough to close discrepancies and release lots, over time the FDA and other agencies will pressure you into making these FIO tests into in-process or lot-release tests.

Defensibility

In the end, your actions in deciding to perform a test need to be defensible.  You need to defend the costs to do the test to management.  You need to defend not doing the test to the FDA.  And your situation may be different than the biologics manufacturer down the street.

That defense ought to rest on whether or not you can do something with the result of the test.

Who Are You Guys, Anyway?

So, I asked for a report to study Zymergi blog readers, and here's where the biotech/pharma readers are coming from:

This is a veritable who's who of the biotech world.  Obviously, you aren't all customers, but when it comes to large-scale biologics support, cell culture and bioreactor contaminations, readers and customers find themselves in good company.

Thanks for reading.

Note: All logos/trademarks belong to the trademark holder and inclusion on this list is not an endorsement of Zymergi or vice versa.

Pros and Cons for Outsourcing Process Development

by Oliver Yu

I visited a contract development and manufacturing organization (CDMO) a few months ago.

What CDMOs do is they develop the process for you. And if you choose, they'll also execute the manufacturing process for clinical or cGMP material.

In short, if you're outsourcing either process development or manufacturing, CDMOs are the people you outsource to (pardon the preposition-ending sentence).

Dan Stark, currently senior director in the Global MSAT group at Genentech, once said (paraphrased):

The winners of the age of biotechnology will be the people who can translate research discoveries into commercial product and those who already have the infrastructure will have a head start.

What he's saying is if you're just a research outfit and you come up with new molecular entities, you're not in the position to extract the full value of that NME. Say you're IDEC pharmaceuticals and you come up with Rituximab... unless you can get the product into the hands of consumers, you're just a research outfit.

Likewise, if you are a contract manufacturer like Lonza where you have the manufacturing know-how and can produce clinical or commercial material, you also are not in the position to extract the full value of your know-how simply because you rely on someone else for your pipeline. In a lot of ways, you're a commodity (see Samsung getting into the biologics manufacturing space with Samsung Biologics).

Dan is saying that the people... the companies who can take a NME through the clinic... through the FDA approval process and be able to make the drug product are the ones who can extract the full value.

So why would anyone with a NME outsource the crown jewels of their business and go with external process development?

It turns out there are a lot of reasons.  To be sure that we got it right, Zymergi has collaborated with Dr. KC Carswell Ph.D of Carswell Bioprocess Consulting to produce a whitepaper on outsourcing process development.

If you're thinking about sending your process development into the hands of a 3rd-party, you definitely need to read the pros and cons of outsourcing.

Get FREE Whitepaper on Outsourcing PD

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

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

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.

Genentech: Beware Lepto Contamination

A year ago on July 19th, 2012, Genentech VP of Biologics Quality (Anders Vinther) presented "A Novel Bacterial Contamination in Cell Culture Manufacturing" at the West Coast Chapter of the Parenteral Drug Association. (This same presentation was likely made elsewhere, but the only "Google-able" mention of it was on the WCC PDA website).

Most biotech/pharma companies are tight-lipped about their biologics manufacturing process problems.

by Oliver Yu
1. For one, they run proprietary processes: it's none of our business.
2. For two, Obamacare forces the FDA to approve a regulatory pathway for biosimilars: why share these growing pains with competitors who seek to eat their marketshare?
3. For three, why air out dirty laundry?

So when Genentech came forward with a very detailed presentation on bioreactor contamination and a prescription for how the rest of the biotech industry to handle this specific type of contamination, it's worth paying attention.

Their summary of events goes like this:

• Visual examination of cell culture indicates contamination of seed cultures
• Gram stain shows no bacteria
• 5-day incubation with standard plate count shows no growth
• No signs of contamination by looking at dO2, pH trends
• No evidence of contamination from standard QC testing methods

This contamination is the black swan event. Never in the history of cell culture manufacturing has anyone encountered a microbe that isn't detectable with standard methods.

Leptospira

After a second seed bioreactor contamination, Genentech was able to cultivate the bug and identify it as Leptospira. Leptospira is a coiled/spiral that survives in soil and water. It is motile, slow-growing obligate aerobe that favors liquid environments.

But the characteristics relevant to biologics manufacturing are:

• 0.1 micron in diameter - CAN PASS THROUGH 0.1 micron filters!
• Non-spore former - Not heat resistant
• Requires long-chained fatty-acid - Will not grow in media alone, requires presence of CHO cells

The remainder of the slides go through their root cause analysis and contamination investigation as well as global risk assessment (i.e. "CYA"). And it's certainly worth a gander.

For us, we would be wise to learn their lessons, which are:

• There's a bug out there that passes through 0.1 micron filters: L. licerasiae
• This bug (and related bugs) are not detectable with standard methods, so LOOK at your cultures!
• Update control strategies (consider heat-treatment and other barriers)

Battling contaminations is bad enough.  Now there's a bug out there that can get by sterile media filters and cannot be detected by no other method than by putting your eyeballs on it.