direct detection of biofilms and cip-related problems in ... · and mirror-polished end cap during...

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Direct Detection of Biofilms and CIP-Related Problems in Liquid Process Systems

Mark Fornalik

Ethox International

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Product Quality & Process Health

• Product quality depends in large part on cleanliness of the liquid product transfer line

• Traditional methods of monitoring system health:– Analyzing final product– Analyzing residual product in process water flush– Swabbing interior surfaces of tanks & lines for biofilms (ATP,

PCR analysis)

• But…..– Most bacteria recovered don’t grow in culture in the microbiology

lab– Analyzing effluent water does not provide any indication of what

remains behind on the pipe wall– ATP and PCR methods require critical cell mass for signal

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Transfer Line Contamination

Contamination Problems:• Cross contamination between

product types• Physical waste – spots,

streaks, particles, filter plugging, viscosity changes

• Chemical waste – chemical contamination of final product

• Increased brand change time• Loss of product flow• Increased production runs to

allow for waste

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Insoluble Wall Fouling• Fouling: The unwanted formation of insoluble

residues on engineering materials in contact with flowing solutions

• Fouling is what is left on wall surface after even a proper water flush clean

• Chemical cleaning must be designed to address water-insoluble wall fouling

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• Organic • Inorganic• Biological (bacteria, fungi, algae - BIOFILMS)• Particulate (corrosion)• Crystallization/Scale (boilers, heat exchangers)• Combination (any two or more of the above)

Insoluble Wall Fouling Types*

* T.R. Bott, * T.R. Bott, Fouling of Heat ExchangersFouling of Heat Exchangers, Elsevier (1995), Elsevier (1995)

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The goal of cleaning is to return the system to the induction periodlevel of fouling

Fouling Rate

time

fou

ling

mas

s

physical

chemical

induction period

secondary fouling

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Fouling Cell: Sanitary Cross with Polished End Caps

Product Flow

Material that adsorbs (sticks) on pipe wall also adsorbs on mirror-polished end caps (fouling cell discs)

Insoluble material deposits on pipe wall and mirror-polished end cap during product flow

Mirror-polished end caps

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Measuring Wall Fouling

Fouled end cap (fouling cell disc)

Fourier transform infrared beam

Spectrum from reflected infrared beam

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FTIR provides a “chemical fingerprint” of the fouling, as well as an indication of fouling amount

Fouling Identification

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Process Cleaning: A Structured Approach

System Design

Water Flush Optimization

Chemical Clean Optimization

Biofilm Control

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0.0001

0.001

0.01

0.1

1

10

100

1000

0 5 10 15 20 25 30 35

Time (minutes)

Per

ce

nt

of

Dye

in t

he

Flu

sh S

olu

tio

n

Magenta

Yellow

Cyan

Insufficient water flush leaves product behind in pipe; optimized water flush reaches “plateau” more

quickly for faster cleaning times

Water Flush Effluent: Product Displacement

Old process water flush end point

Water flush “plateau “

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Powerflush (Two-Phase Flow)Cleaning

Cleaning efficiency varies as a function of the ratio of air flow to water flow

Efficient flow ratio Water-rich flow ratio

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Measuring PowerflushCleaning Efficiency with FTIR

-0.0010

-0.0005

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

0.0040

0.0045

0.0050

0.0055

0.0060

0.0065

0.0070

0.0075

0.0080

Abs

orba

nce

1000 1500 2000 2500 3000 3500

Wavenumbers (cm-1)

-0.0010

-0.0005

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

0.0040

0.0045

0.0050

0.0055

0.0060

0.0065

0.0070

0.0075

0.0080

Abs

orba

nce

1000 1500 2000 2500 3000 3500

Wavenumbers (cm-1)

Peak height data correlate to effectiveness of cleaning: the smaller the peak, the more effective the cleaning

Before powerflush

After powerflush

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Chemical Cleaning Variables

� Chemical cleaner formulation� Concentration� Temperature� Order of addition

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Measuring Chemical Cleaning Efficiency

0%

20%

40%

60%

80%

100%

TSP NaOCl TSP/NaOCl NaOH Citric acid

clea

nin

g e

ffic

ien

cy

FTIR peak height before & after cleaning provides an estimate of

cleaning efficiency

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Studying Chemical Cleaning Parameters

0%10%20%30%40%50%60%70%80%90%

100%

25 C 45 C 65 C5% NaOH

clea

nin

g e

ffic

ien

cy

Impact of temperature

0%10%20%30%40%50%60%70%80%90%

100%

0.2% 1.0% 5.0%NaOH wt% @ 60 C

clea

nin

g e

ffic

ien

cy

Impact of concentration

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• Unwanted adhesion of bacteria or other organisms onto surfaces of solution-handling systems

• Not necessarily uniform in space & time• May contain significant amounts of inorganic

materials held together by the polymeric matrix

*(Charackis & Marshall, Biofilms, 1990)

Biofouling/Biofilms*

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Biofilm-Related Contaminants

• Cells (possibly pathogenic)• Anions (acetate, formate, nitrate, etc.)• Proteins, glycoproteins, carbohydrates,

fatty acids• Enzymes• Surfactants• Organic and inorganic particles• Substrate degradation (metals, plastics)

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Biofilm Resistance to Cleaning• Standard CIP methods may not remove biofilm

• Biofilms able to grow after 8 months desiccation• Biofilms withstood 80C or higher water

temperatures• Biofilms withstood 20, 50 and 200 ppm chlorine,

25 ppm iodine∗ Food Protection Report, 7(5):8 (1991)

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Standard Methods to Measure System Health & Cleanliness

• Product testing:– Taste– Chemistry– Plating/culturing

• Process testing:– Cleaning water effluent testing

• Plating• Residual product

– Swab testing by plating– ATP and/or PCR testing

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Key Points

• Biofilms exist in chemical as well as water transfer lines

• Biofilms can alter the chemistry of the product or water going through the line

• Biofilms can evade detection by traditional microbiological testing methods because these methods focus on recovering and growing cells from biofilms

• Fouling cell technology relies on measuring exopolymer, not necessarily cells, in place on the surface of interest, avoiding inefficient scraping and culturing methods

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Bacteria Populations in a Pipe

99%

1%

TRADITIONAL SAMPLING: 1% of total bacteria population inside of pipe is planktonic (free swimming organisms from bulk solution)

FOULING CELL SAMPLING: 99% of total bacteria population inside of pipe is sessile (attached biofilm on the wall of the pipe)

Sessile organisms (biofilms) can be very resistant to cleaning

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1 day 2 days

9 days4 days

45°C Ultrapure Water Biofouling

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Biofilm Chemistry Over Time*Subtraction Result:ir1848, 610 NRX disc #26, 3-month exposure, no clean*Subtraction Result:ir1896, 610 NRX, 14 batches (4 days), disc #7 (1/30 - 2/2/98)*Subtraction Result:ir2288, 610, NRX, #10, 24 hours, 5 batches, 2/26 - 2/27/98*Subtraction Result:ir1974, disc 10, 610 NRX, 1 batch, 4 hrs, without santoprene gasket

-0.008

-0.007

-0.006

-0.005

-0.004

-0.003

-0.002

-0.001

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0.011

0.012

0.013

0.014

0.015

0.016

0.017

0.018

0.019

0.020

Abs

orba

nce

600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000

Wavenumbers (cm-1)

Biofilm changes to cleaning-resistant exopolymer upon aging

2 hrs

8 hrs

24 hrs

6 mo

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Biofilm Resistance to Cleaning: Bleach Treatment

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Mapping Process CIP Efficacy in a Brewery

FTIR & epifluorescence of fouling cells can provide cleaning efficacy data from end to end of a process

FTIR spectra of fouling cells placed in 5 locations of a manufacturing process (stage A through E) for 8 weeks

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Process Mapping in a Brewery: FTIR Peak Heights by Location

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

A B C D E

abso

rban

ce u

nit

s

PackagingProcess Start

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Brewery Wort Line

2 weeks, 100x objective 8 weeks, 100x objective

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

A B C D E

abso

rban

ce u

nit

s

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Brewery Aging Line

2 weeks, 100x objective 8 weeks, 100x objective

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

A B C D E

abso

rban

ce u

nit

s

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Brewery Filler Inlet Line

2 weeks, 100x objective 8 weeks, 100x objective

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

A B C D E

ab

sorb

an

ce u

nit

s

FTIR determines onset of biofouling in process

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Brewery Filler Inlet Line

8 weeks, 100x objective 8 weeks, 100x objective

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Winery Bottling Line 1 After CIP

1-week exposure, 100x 4-week exposure, 100x

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1-week exposure, 100x 4-week exposure, 100x

Winery Bottling Line 2 After CIP

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After water flush After CIP

Removed by CIP

Not Removed by CIP

Winery Bottling Line 2 Before & After CIP

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Biotech Company Fermentation

2-day exposure before CIP

2-day exposure after CIP

4-week exposure after CIP

CIP: 5% NaOH, 65°C, 30 min daily

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Biotech Company Recovery

2-day exposure before CIP

2-day exposure after CIP

4-week exposure after CIP

CIP: 5% NaOH, 65°C, 30 min daily

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Fermentation vs. Recovery

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Pharma Company Steam System Diaphragm Valve

Areas selected for analysis

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Pharma Company Steam Valve Stereo Microscopy

40X

Organic material

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Pharma Company Steam Valve Confocal Microscopy

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Pharma Company Steam Valve Confocal Microscopy

Region of heavy fouling

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Pharma Company Steam Valve Atomic Force Microscopy

Height image Phase image

Apparent scale formation

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Pharma Company Steam Valve Atomic Force Microscopy

Height image Phase image

Apparent organic material (biofilm exopolymer)

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Process Cleaning Improvement Flow Chart

On-site process assessment:

• system design

• water flush parameters

• wall fouling

Fouling cell studies to determine:

• fouling chemistry

• fouling rate

• presence of organisms

Lab cleaning studies to determine:

• appropriate cleaning chemicals

• chemical concentration, temperature

• chemical contact time, order of addition

Process trials with new cleaning procedure:

• implement new cleaning procedure

• verify improvement

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Conclusions

• In-line fouling cells can provide:– An early warning for issues of process cleanliness

and health– Information on chemistry and rate of fouling within

system– Objective data on CIP efficacy– Ability to determine efficacy of proposed cleaning

changes in the lab, not in production– Ability to screen new products for fouling propensity

• These methods are complimentary to existing process health measures