Sunday, June 30, 2013

Examples of Cell Culture Productivity KPIs

Let's apply what we know of cell culture productivity KPIs.

Below is a control chart of a process that produces a stable, albeit variable titer:
control chart of titer
The titer is a very simple data point to collect. QC measures it following their procedures and they spit out this one number every time a sample gets submitted.

Time required at the production culture stage to achieve this 2g/L is 10 days give or take a few hours.control chart of culture duration
The culture duration is also relatively easy to determine since we know the timestamp of inoculation and we know the harvest time. An arithmetic subtraction is all that is required to find this number.

Culture Volumetric Productivity

The culture volumetric productivity is computed by dividing titer by culture duration.control chart of volumetric productivity
It stands to reason that control chart of culture volumetric productivity shows a stable, in-control KPI.

It turns out, there was a scheduled facility shutdown after Run 8. And starting with Run 9, there was a mis-specified parameter that determines the fermentor volume.control chart of culture volume
Our control chart shows special cause signals from Run 9 - 12 indicating that it took 4 batches before the QA Change Control system was able to push through the change.

Capacity-based Volumetric Productivity

By including bioreactor volume - which is determined by load cells or radar and known to the control system's process historian - we can compute capacity-based volumetric productivity:
control chart of capacity-based volumetric productivity
If you look at it, the control chart for capacity-based VP doesn't look that different from the culture VP. Even with runs 9 - 12 at 83% capacity, there is still no obvious, control-limit-violating-special-cause signals.

The shutdown lasted seven days  and you can see that even though the bioreactors were cleaned and sterilized, they were left fallow for several days before the plant went back into production. The turn time spikes
control chart of turn time
Let's have a look at plant-based volumetric productivity.

Plant-based Volumetric Productivity

control chart of turn time
Again, we see here that runs 9-11 show a depressed plant-volumetric productivity, but still no obvious control chart violations. Plant-based volumetric productivity is a lot harder to compute since you're talking non-row data (in the SQL sense).

Typically, your manufacturing control system (MCS) is enumerating UnitProcedures and storing each UnitProcedure in their own row. To compute the turn time, you actually have to list out the previous several UnitProcedures and find the previous harvest and reliably getting this data is a pain in the butt.

Plant-based volumetric productivity violates Principle #2 of MSAT data:
The benefits derived from collecting the data needs to out-weight the costs.
In this case, for this operation where variability in other parameters are relatively high, all this extra work doesn't give you much that much benefit.


In the perfect world, data is easy to get and KPIs tell you a lot. In reality, it may tell you that you need to reduce your process variability before your KPIs are worth collecting.

Alls I'm saying is that you need not forge ahead and apply every KPI that you learn about. In some cases, getting the data may cost more than the data is worth.

Related articles:

Thursday, June 27, 2013

How to Measure Cell Culture Productivity

So I've written about key performance indicators (KPIs) for cell culture in the past. And the KPI depends on whether you're talking seed/inoculum vs. production culture.

Final Specific Growth Rate

To recap, if you're in charge of monitoring seed/inoculum cultures, your goal in life is to deliver a specific amount of cells in the growth phase; therefore, your goal is to have a high final specific growth rate.

final specific growth rate
Compute specific growth rate by taking the slope of the natural log of the biomass against time.

Culture Volumetric Productivity

If you're in charge of production culture you want to have as high a concentration (of product) in as short a time as possible. Therefore, you seek a high volumetric productivity, which is:

For lab- and pilot-scale operations, this KPI is just fine.

Capacity-based Volumetric Productivity

For large-scale, commercial cell culture, however, volumetric productivity of the culture misses the mark and here's why:

Suppose you had a 2.5g/L process and you were able to get that in 10 days. Your volumetric productivity is 0.25 g/L/day. If your working volume is 10,000L this means you have 2.5 kilos of product.

Well, if your bioreactor is a 10kL, then you're making as much product as possible. But if your bioreactor is a 12kL, then you're not using your capacity to the fullest. This is why a better metric is capacity-based volumetric productivity:

In situations where your plant is always running, there's another metric.

Plant-based Volumetric Productivity

Even though culture duration (harvest timestamp - inoculation timestamp) is the only period when the product is being produced, the total time consumed should include the time spent cleaning, sterilizing and prepping the bioreactor. The time spent turning a dirty bioreactor (from the last harvest) to a prepped bioreactor is called the turn time, and when you include that into the equation, you get a true measure for the productivity of your biologics manufacturing plant called plant-based volumetric productivity:


Plant-managers are fine knowing the final titer or just the total culture mass since titer is just a single number coming out of QC and culture mass is what you're accountable for.

But if your team of cell culture scientists/engineers in MSAT are interested in comparing cultures on an apples to apples basis, they had better be control charting volumetric productivities.

Wednesday, June 26, 2013

If Kryptonite is Root Cause, What's the CAPA?

Superman is out there beating up and capturing your above-average-IQ'ed criminals. What do you suppose his success rate is?

100%, right?

I mean, how do you go up against a guy who can fly, has heat-ray vision, X-ray vision and can withstand all applications of the Second Amendment?

superman kryptonite
Superman succumbing to kryptonite
Answer: You can't.

But suppose Superman pits himself against an evil genius,  say Lex Luthor, who discovered that Superman loses his powers upon exposure to kryptonite.

Superman's success rate just plummeted to 0%.

Were he to perform an analysis while floating around helplessly in a pool of water with kryptonite chained around his neck to identify the root cause of his downfall, what do you suppose the most probable cause (MPC) would be?

  • Would it be the gullibility of honest/small-town upbringing?
    If so, this wouldn't explain his high success against other criminals.

  • Would it be Lex Luthor's cunning?
    If so, this root cause could not explain the supervillain Brainiac of similarly high intellect.

  • Would it be the kryptonite?
Most people would stop here and say the true root cause of his new low-success rate would be the kryptonite itself. Take away the kryptonite and Superman is back to 100% success. Bring back the kryptonite:  0%.

But if the Son of Jor-El assigned blame to kryptonite, what's the CAPA?

 A federal regulation banning the possession of kryptonite?  Federally-licensed kryptonite dealers?  Universal-background check on kryptonite purchases?

See, I say the true root cause is Superman's pre-existing condition that makes him vulnerable to kryptonite. If you (somehow) take away this vulnerability, Superman would have 100% success all the time.

If he hired me to increase his success rates, I'd craft a super-suit made of lead. The extra bulk would not encumber him given his strength nor would he be susceptible to lead poisoning. Maybe throw in lead face-paint, lead gloves and lead boots to deflect the radiation from the kryptonite.

The key to a permanent increase in success rates may be to challenge conventional thinking and to address pre-existing vulnerabilities in your process--no matter how much success your process delivered in the past.

See also:

Friday, June 21, 2013

Where To Get 483s

If you're manufacturing a product that is regulated by the Food and Drug Administration, be it a food, a drug, a medical device, an X-ray machine, or a condom, you are subject to inspection by the FDA.

There's what I call an FDA Enforcement Funnel.

fda enforcement funnel
At the top of the funnel are cGMP facilities that get inspected. Inspectors come by, they audit your facility, they find nothing to worry about and they leave. You can sigh relief and be on your way. They'll be back in more or less 2 years.

The next step down this funnel is when the audit generates observations. Inspectors will write these observations down in what's called a Form 483... a.k.a. ("483"). As the recipient of the 483, the ball is in your court. You need not actually respond, but responding is actually a pretty good idea because your well-reasoned, timely response can help you avoid a warning letter.

An FDA warning letter is a communication that the Food and Drug Administration is serious and they will seek enforcement action. You'll get these if your inspectional observations are serious enough... or if repeated inspections reveal no actions are taken to assuage the FDA that you're taking quality seriously.

If the warning letter produces low-impact results, the FDA will use the weight of law to coerce you into compliance via a Consent Decree... where in lieu of legal action, they get you to volunteer... in writing... to fix your compliance problems.

In biologics manufacturing, getting a 483 is the first step down the slippery slope of FDA enforcement action. You're not going to be dealing with consent-decrees if you haven't gotten warning letters. You're not getting warning letters about cGMP issues if you haven't gotten 483s. So focus on not getting 483s.

How do you avoid 483s? Well, there are armies of QA and regulatory professionals trying to answer that question.

One way is to get some intel on the 483s that the FDA has previously issued. The FDA releases a limited set of redacted 483s here. These 483s are scanned PDF files that are often requested or in the news (remember the 2012 Eggs or 2013 Pharmacies?)

What if a 483 you're interested in isn't there? Well, you can submit a Freedom of Information Act (FOIA) request to the FDA, fill out their form, email back and forth with an FOIA specialist and get your PDF file in several weeks.

- or -

You can browse the FDAzilla 483 Store to search for a 483... or even browse 483s by inspectors to get a sense of where each inspector likes to focus.

As my QA brethren (Thats you, Barlow and Zucca) like to remind me, producing successfully harvested cell cultures isn't the point. Producing releasable lots of drug product is; and producing releasable lots means compliantly (as deemed by the FDA) operating a GMP environment.

See also:

Thursday, June 6, 2013

Bertrand's Box Paradox

The Bertrand's Box Paradox refers to this puzzle:

You have 3 boxes before you.
  • Box A contains two gold coins.
  • Box B contains one gold coin and one silver coin.
  • Box C contains two silver coins.
Like so:
Box A
Box B
Box C

Question: Suppose you chose a box at random and withdrew one gold coin. What are the chances that the next coin is also gold?

Well, If I withdrew a gold coin from one a random selection of the three boxes, then I must have either Box A or Box B. Since I have two remaining choices: one favors a gold coin and the other favors a silver coin, then the chances of me pulling out a gold coin is 50% (aka 50/50).

Box A
Box B

Seems like it should be, right? Turns out it's wrong.

Here's how I wrangled this problem. I did it by using differing gold and silver coins.

Box A
Box B
Box C

So 3 boxes at 2 coins a piece means there are actually 6 possible outcomes in which I can randomly select a box and pull out coins.  Here they are:

1st coin2nd coin
1 Choose Box A and snag the Gold Eagle first.
2 Choose Box A and snag the Gold Buffalo first
3 Choose Box B and snag the Gold Eagle first
4 Choose Box B and snag the Silver Eagle first
5 Choose Box C and select the Silver Eagle.
6 Choose Box C and grab a Silver coin.

These are my only six options. Per the paradox, I withdrew a gold coin first and not a silver coin. This means that I didn't pick Box C's two possibilities.  It also means that I didn't pick one of two Box B possibilities.

Essentially, I have three possibilities left:

1st coin2nd coin
1 Box A: Gold Eagle first, then Gold Buffalo
2 Box A: Gold Buffalo, then Gold Eagle
3 Box B: Gold Eagle, then Silver Eagle

From here, it's pretty easy to see that my second coin has two out of three chances of being gold and one out of three chances at being silver.

And thus correct answer to Bertrand's Box Paradox is 2/3 or 66.67%.

Why does this talk of probabilities matter to a Manufacturing Sciences team or cell culture engineer?

Well, understanding the math behind bioreactor contamination, or recovery step yields, is one of the foundations in explaining real phenomena. This matters is because your biological system is multivariate.

Not only that, your process steps are sequential: Production cultures come after inoculum cultures; arvests after production cultures; ProA after harvest and so on and so forth. The success of this step often depend on the outcome of the previous step. And CofA attributes measured at a late purification step could be caused by some factor at the production culture stage.

Large-scale biologics manufacturing is complex, far more complex than picking a box with two coins and pulling them out one at a time. Yet the math behind the Bertrand's Box Paradox shows us that we muggles are susceptible to missing the mark when conditional probabilities are involved.

Credits: Images are from the US Mint and therefore in the public domain.