A Bit of Extra Lab Effort Can Prevent Grief During Scaleup

7/28/2019 A Bit of Extra Lab Effort Can Prevent Grief During Scaleup

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Its an old saw, but Ive long heldthat process development is verymuch a team effort. Developing

safe, robust and scaleable chemicalprocesses calls for close collaborationbetween synthesis chemists, processdevelopment engineers and pilot plantpersonnel. But experience shows that,particularly in many fine chemicaland pharmaceutical organizations, re-searchers fail to put this principle into

practice until its too late.

Finding out in the process Hazopthat the environmental permits pro-hibit the use of your chosen extractionsolvent in your companys pilot plantis no laughing matter. Nor is arrivingat the contract manufacturers site forthe project only to learn that the desig-nated equipment is not set up for vac-

uum distillation (it happened to me!).Attention to just such mundane

details is, unfortunately, still an im-portant part of process technologytransfer and scaleup. Clearly, goodcommunication is the key ingredientto minimizing such painful experi-ences. However, the more glamorous

role of process development, at leaston paper, is the collection of quanti-tative data on process performanceto help streamline the scaleup effort.This is where experienced engineersand their colleagues can really shine.

Its unfortunate that some synthe-sis chemists, their minds focused on

the latest asymmetric catalysis break-through or planning their next ligandscreening study, show little interest inthinking about collecting scaleup data.

Admittedly, so many projects die in

the early stages that chemists can ill

afford to conduct detailed engineeringstudies, nor do they get paid to do so.But most do not realize how little ef-fort they would have to expend to col-lect a few valuable data points alongthe way while they work. A littledata, correctly interpreted, can staveoff scaleup disasters down the road.

Might I suggest that such individualsonly need a good engineering mentorto help them see the light?

Many examples come to mind. Eventhings as simple as recording densitiesof the various process streams, or par-tition coefficients of key compounds,can prove invaluable in closing mass

balances, calculating volumetric pro-ductivity and developing a cost model.Recording pot temperature and oper-ating pressure during batch distilla-tions can help establish important op-erating parameters for scaleup, ratherthan just leaving them to chance.

In this article, I consider two exam-

ples of simple laboratory-scale studiesthat can help head off potential prob-lems in that first pilot run. Both in-

volve solid-liquid separation processes

isolation of a crystalline solid from

a slurry by batch filtration or centrifu-

gation, and the drying of said solid ina batch contact dryer. Both examplesalso illustrate that in this age of ad-

vanced instrumentation and onlineanalysis, simple low-cost test methodsstill have great value.

Solids isolationIt certainly is true that many seriousproblems are encountered for the firsttime only in the pilot plant, but thereare usually quantifiable physical rea-sons for this. Sometimes, the reasonsinvolve poor reaction selectivity due tothe very different mixing environmentfound in large processing vessels, or

extended processing times at largescale. But often, problems arise sim-ply due to inexperience or the failureto quantify some basic physical prop-erties of the process streams involved.Such problems can create significantdelays in the program, and can evenkill an otherwise promising project

with a tight timeline.Anyone who has ever transferred

a process from the laboratory to thepilot plant can vouch for the fact that

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38 CHEMICAL ENGINEERING WWW.CHE.COM MAY 2006

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FIGURE 1. Filtration timetypically behaves quadrati-cally (left). Such plots canbe linearized by factoringout the filtrate volume, V.The slope and intercept arerelated to the cake resis-tance and the intrinsic filtercloth resistance (see text)

Francis X. McConville, Impact Technology Consultants

A Bit of Extra LabEffort Can PreventGrief During Scaleup

The key is persuading the chemist

to undertake a little extra data collection

Francis X. McConville


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everything in the plant takes longer

often much, much longer. Productisolation is a perfect example. Manypharmaceutical and fine chemical in-termediates and products are crystal-line materials isolated by centrifuga-

tion or vacuum or pressure filtration.Equipment limitations being whatthey are, it is often necessary to iso-late a crystallization batch in a centri-fuge or filter in multiple loads. I havepersonally experienced what was a5-minute filtration in the laboratorytaking nearly 24 hours to complete

at the 2,000-gallon scale. If ours had

been a more poorly-filtering product,that time might have been 48 hours or longer.

What might be happening to theslurry in the crystallizer during allthat time? Without the proper studies,its anyones guess. Thats why it canbe critical to quantify solids filterabil-

ity, which is typically accomplished ina couple of different ways. The veryfirst thing to do is a slurry settlingtest, which is just what it says turnoff the mixing and allow a sample ofthe slurry to settle on the bottom ofthe vessel. If the solids settle readilyleaving a clear supernatant phase,

that is a good sign that the materialmay filter well.

Another method is to conduct a sim-ple cake-permeability test. Prepare afilter cake about 5 cm (2 in.) deep in aBchner funnel using vacuum, collectthe mother liquors, then pour thoseclear mother liquors back through

the cake and measure their flowrate.A common rule of thumb states that aflowrate of at least 40 L/min/m2 under

vacuum is desired. Anything slower

than that indicates a potentially prob-

lematic filtration on scaleup.A more formal approach is to de-

termine the specific filter-cake resis-tance, usually designated by andexpressed in units of kg/m.

Filtration under constant drivingforce, such as vacuum filtration, gen-erally fits a parabolic profile, whichlooks something like the first plot inFigure 1. The behavior is described bythis relationship:

t = aV2 + bV (1)

where V is the filtrate volume (m3)

and t is the time (s). This quadradicbehavior reflects the fact that as thecake depth increases, the flowrate ofmother liquors decreases. Equation (1)can be linearized by factoring out V:

t/V= aV+ b (2)

which, when plotted, gives a straight

line with slope a and y-intercept b asshown in the second plot of Figure 1.The slope and intercept, which aredetermined by linear regression, arerelated to the cake resistance, , andthe intrinsic filter cloth resistance,

RM

, according to the following classi-cal definitions of the constants:

a = c/2A2P (3)

b = RM/AP (4)

Here is the specific cake resistance(m/kg), is the mother liquor viscos-ity [kg/(m)(s)], c is the concentration ofsolids in the slurry (kg/m3), A is the

filter area (m2), P is the pressure dif-ferential driving the filtration (Pa orN/m2), and finally RM is the specificfilter cloth, or filter medium, resis-

tance (m1). It should be pointed out

here that these relationships must beapplied to the instantaneous volumet-ric flowrate t/Vversus V, extrapo-lated from the raw data (see Table 1).Of course, it is critical that all quanti-

ties be expressed in the proper units.The data collection itself is fairly

straightforward; all that is required isa stopwatch and a properly graduatedfiltrate receiver, or if using positive fil-tration pressure, a filtrate receiver ona balance. Good technique is requiredto obtain meaningful numbers, and

it may be necessary to throw out the

first data point if the system hasntstabilized. If the filtration rate is toorapid, the pressure can be reducedusing a vacuum controller or pressureregulator as necessary.

Table 1 and Figure 2 show sometypical data for a filtration using acontrolled vacuum of 55,200 Pa (551

mbar, 414 mmHg vac), the derived in-stantaneous rate data, and the resultsof the regression to determine both and RM (busy chemists may wish toleave the data manipulation to theirengineering colleagues, but the impor-tant point here is to collect the data).

Typical ranges of are ~108 m/kg

for fast filtering materials to ~1012m/kg for more poorly behaved solids.Testing several filter media is alsoa worthwhile idea if it appears thatthe cloth is a rate limiting factor. Awide variety of woven and non-wovencloths in a variety of materials, poresizes and structures are available, and

some are more prone to blinding insome situations than others.

We are now equipped to predictfiltration performance at large scale,

CHEMICAL ENGINEERING WWW.CHE.COM MAY 2006 39

TABLE 1. RESULTS OF A FILTRATION EXPERIMENTAND ASSOCIATED CALCULATIONS

Filtration data:

Total vol-ume, mL

Time, s Total vol-ume, m3

Average vol-ume, m3

t/V,s/m3

0 0 0

100 5 0.0001 0.00005 50,000

200 25 0.0002 0.00015 200,000

300 55 0.0003 0.00025 300,000

400 93 0.0004 0.00035 380,000

500 140 0.0005 0.00045 470,000

600 198 0.0006 0.00055 580,000

700 266 0.0007 0.00065 680,000

Experimental Conditions:Filter diameter: 7.0 cmFilter area: 0.00385 m2

Slurry concentration:12.0 g/L = 12.0 kg/m3

Filtrate viscosity (est.):20 cP = 0.020 kg/(m)(s)Filtration pressure:-8.0 psivac = 551 mbar = 55,144Pa = 55,144 kg/(m)(s)2

Calculation results:Slope, a = 9.51E+08 s/m6

Intercept, b = 5.44E+04 s/m3

Specific cake resistance, =6.47E+09 m/kgFilter medium resistance, RM=5.77E+08 m1

FIGURE 2. Shown here is a linearized plot of the filtrationdata from Table 1. It is often necessary to ignore the first datapoint in the calculation of slope and intercept


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since specific cake resistance is an in-tensive property of the slurry and notscale-dependent, assuming of course

that the large-scale crystallization hassuccessfully generated the same par-ticle size distribution (psd) and crystal

habit as the laboratory operation (atopic beyond our scope here).

At any rate, bench scale valuesin the range of 10111012 should bea cause for concern. The good newsis that you now have an excellentyardstick by which to gauge the suc-cess of the crystallization studies that

you may subsequently undertake toimprove filtration performance. Thegoals of such work should be to nar-

row the particle-size distribution, re-duce the number of fines and generatea larger mean particle size. Varioustechniques, such as cooling profile ma-nipulation, temperature cycling and

slurry aging, to name just a few, are atyour disposal for achieving this goal.For further reading on crystallizationprocess design see References [14].

Couple this with a photomicro-graphic record of the results of variouscrystallization experiments, perhapsthrow in a bit of particle size analy-

sis, and youve got yourself a nice little

crystallization study. But more impor-tantly, you have taken a major step to-ward preventing a painfully slow andtroublesome filtration in the plant,and the many consequences thereof,such as particle attrition, product deg-radation and unwanted polymorph in-terconversion, among others.

There are, of course, many more ad-vanced techniques available for study-ing crystallizations, such as on-lineparticle size analysis via FBRM (laserdiffraction), PVM (visual microscopy),and pressure filtration studies, whichcan be important for identifying fil-ter cakes that are highly compress-

ible, and therefore poor candidates forcentrifugation, and for selecting thebest filter media for the process. ButI think weve demonstrated that onesimple laboratory measurement cangenerate a lot of information. Furtherreading on these techniques can befound in References [511].

Product dryingLets turn our attention to anothertype of laboratory study that requires

little effort but can be invaluable in

identifying potential scaleup issues inproduct drying.

As weve said, everything takes longerin the plant, and drying is no exception,especially in the ubiquitous vacuum-tray dryer. Deeper cakes, in contactwith the heated surfaces of contactdryers for extended periods, and longer

heat-up and cool down times, can spelltrouble. Batches subjected to prolongeddrying cycles at elevated temperatures

are prone to all manner of undesiredbehavior from polymorph intercon-

version in the wet cake, agglomerationand product degradation to runawayexothermic decomposition.

Solids drying is characterized by aseries of internal and external resis-tances to solvent removal. By perform-ing a simple drying study, we can iden-tify which of these various resistancesis the controlling factor in our particu-lar product. This type of study fits ourprofile perfectly you were going to

dry the material anyway; why not col-

lect a few data points along the way?In a nutshell, we need to monitor

the progress of the drying operationby collecting some data on the wetcake weight versus time. This can beaccomplished in a variety of ways.Some have reported success conduct-ing the drying study in a flask on a ro-

tary evaporator (rotovap). PersonallyI think the ideal approach is to dryin a vacuum-tray dryer on a balanceinstalled right in the oven, eliminat-ing the need to break the vacuum toremove the cake and weigh it.

However the data are collected, oneshould expect the cake to lose weight

rapidly early on and more slowly to-ward the end of the drying cycle. Byplotting the data, as discussed below,one can identify the various stages ofdrying and the resistances associatedwith each of those stages.

Lets assume, by the way, that priorto this work weve already established

a specification for our final moisturecontent. Do not assign this specifica-tion arbitrarily. Time is money, anddrying can be a real process bottleneck.

Do not target extremely low moisture

content when some higher value maybe perfectly acceptable, particularlyin the case of intermediates (do theyneed to be dried at all?).

As in the above filtration case, it isthe instantaneous drying rate datathat will be of most use to us in identi-fying the drying stages. Therefore the

wet cake weight versus time must bereduced to change in solvent content

versus time.

By plotting the instantaneous ratedata, we can readily identify severalkey stages in the drying process. Ini-tially, the moisture being removedfrom the cake is surface moisture

residing on or between the crystalparticles. This unbound moisture hasessentially the same enthalpy of va-porization and boiling point as the freeliquid would at the given operatingpressure. Except for perhaps a briefwarm-up period, the evaporation rateat this stage is essentially constant,

limited by the rate of heat transfer

to the wet cake. This constant rateperiod, not always apparent from theraw data, is evident in a plot of dryingrate versus time, as shown in Figure3. The drying rate during this periodis not particularly product-dependent,especially for crystalline materials.

The moisture content at the end of

the constant rate period is called thecritical moisture content, or some-times the transition moisture content.This point in the drying curve repre-sents a transition from surface solventremoval to a stage of drying that is

very much dependent on the charac-teristics of the product itself. For in-

stance, in a highly porous material, asignificant amount of solvent can betrapped within the crystals. But thissolvent has an effective boiling pointmuch higher than the free liquid, dueto attractive capillary forces and slow-ing rates of evaporation as the liquidin the pores changes from a continu-

ous liquid phase filling the pores intonon-contiguous droplets of liquidin the pores. This stage of drying iscalled, appropriately enough, the fall-

FIGURE 3. An exampleof a theoretical dryingcurve is shown on theleft. The various stagesof drying can be mademuch more evident byplotting the rate of dry-ing versus time (right)

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ing rate period, reflecting the fact thatthe more and more tenacious solventremains in the later stages.

Moisture trapped in occlusionswithin the crystal body would be thenext to evaporate. Removal of this sol-

vent is likely to be diffusion limited, andone might detect this in a secondary

critical moisture content in the dryingcurve and a transition to a second fall-ing rate stage. The final stages of dry-ing may include stripping solvent froma crystal solvate or hydrate some-times not the desired result of drying,and so understanding where this stageoccurs and the conditions that bring it

about can be most important.

Table 2 provides some typical datafrom a vacuum-tray-dryer experi-ment. The data are plotted in Figure 4,which illustrates that one can obtaingreater differentiation between thedrying stages by plotting drying rate

versus solvent content, as shown. But,again, the take-home message is that

we can learn a great deal about dryingbehavior by conducting a relativelysimple drying study if the data are

gathered and we do the study.Lets consider some possible scenar-

ios. If the majority of the drying time oc-curs in the constant rate period, we mayinterpret this to mean that there is little

moisture within the crystals, and we aresimply limited by evaporation of the freemoisture. In such a case, we may be able

to significantly speed drying if we canobtain a larger mean-particle size at thecrystallization step, or perhaps attemptto reduce wet cake solvent content byusing centrifugation with a long deli-

quoring spin cycle, instead of vacuumfiltration. Other options might includeconducting a final cake wash with alower-boiling solvent or even a mini-mum-boiling azeotropic solvent mixtureto speed solvent removal in the dryer.

If, however, the constant rate periodis relatively short, and the majority of

the drying cycle is taken up removing

solvent trapped within the crystals,then the above techniques would havelittle effect on the total drying time.Instead, you may need to do morework on the crystallization step toachieve purer crystals with less en-trapped solvent. Maintaining bettercontrol over the nucleation and crys-

tal growth steps using a well-designedseeding protocol and manipulatingthe cooling or antisolvent additionprofile to maintain constant supersat-uration throughout the crystallizationare common ways of approaching this.For further reading on this topic, seeReferences [5, 6, 12].

Final remarksI have tried to show in this articlethat quantitative information on the

filtration and drying behavior of solidchemical products can be very helpfulin predicting process performance atlarge scale. But more importantly, col-lecting such data at laboratory scale is

often neither difficult nor particularlytime consuming. Much has been writ-ten about controlling crystallizationsand many advanced techniques existfor studying and characterizing thematerials so produced. But utilizingthese tools effectively means establish-ing a baseline for performance to help

set the goals for further development.

Naturally, the value of gathering labdata and establishing a baseline forperformance can apply to other chemi-cal process operations besides filtra-tion, drying and crystallization. Veryoften, simple laboratory studies thatrequire little time or effort can provide

valuable insight into the physical and

chemical mechanisms at work in yourprocess.

Edited by Gerald Ondrey

FIGURE 4. This plot of drying rate versus moisture content(data from Table 2) is particularly useful for identifying thevarious drying stages

CHEMICAL ENGINEERING WWW.CHE.COM MAY 2006 41

TABLE 2. DATA SHOWING THE PROGRESS OF DRYINGA WET-CAKE SOLID IN A VACUUM-TRAY DRYER

Time,min

Grossweight, kg

Net weight,kg*

Wt.%solvent**

Drying rate,g/min

0 5.830 27.80 23.0

60 5.766 2.716 20.2 1.07

120 5.702 2.652 17.3 1.08

151 5.669 2.619 15.9 1.05

240 5.578 2.528 11.8 1.03

360 5.520 2.470 9.3 0.48

480 5.480 2.430 7.5 0.33

1,020 5.385 2.335 3.3 0.18

1,260 5.351 2.301 1.8 0.14

1,360 5.342 2.292 1.4 0.09

1,462 5.335 2.285 1.1 0.06

1,656 5.325 2.275 0.6 0.05

*Tare weight of the tray = 3.050 kg**Calculated based on a final dry-cake weight of 2.260 kg

AuthorFrancis McConville is asenior consultant for Im-

pact Technology Consultants(9 Tabor Hill Road, LincolnMass. Phone: (508) 951-2436;Fax: (718)-240-7688; Email:[email protected]) and has aprivate consulting business,FXM Engineering & Design(Worcester, Mass.). He is theauthor of The Pilot Plant RealBook A Unique Handbook for

the Chemical Process Industry, and is an instruc-tor for the Scientific Update professional trainingcourse, Secrets of Batch Process Scale-Up. He hasover 25 years experience in the process industries,including 14 years as a pharmaceutical process-development engineer at Sepracor, Inc. (Marlbor-ough, Mass.). McConville holds a B.S. degree inchemistry and M.S. degrees in biotechnology andchemical engineering from Worcester PolytechnicInstitute. He is a member of the ACS, ISPE and alifetime member of AIChE.

References1. Botsaris, G. and Toyokura, K., Separation

and Purification by Crystallization, ACS,N.Y., 1997.

2. Mullin, J. W., Crystallization, 4th ed., But-terworth-Heinemann, Oxford, 2001.

3. Mersmann, A., ed, Crystallization Technol-ogy Handbook, Marcel-Dekker, N.Y., 1995.

4. Davey, R.J. and Garside, J., From Moleculesto Crystallizers, An Introduction to Crystal-lization, Oxford Science, N.Y., 2000.

5. Chopey, N. P., ed, Handbook of Chemical Engineer-ing Calculations, 3rd ed., McGraw-Hill, N.Y., 2003.

6. McCabe, W., Smith, J. and Harriott, P., Unit Op-erations of Chemical Engineering, McGraw-Hill,N.Y., 2004.

7. Wakeman, R.J., and Tarleton, S., Solid/Liq-uid Separation, 1st ed. Principles of Indus-trial Filtration, Elsevier, N.Y., 2005.

8. Purchas, D. Industrial Filtration of Liquids,2nd ed., Leonard Hill Pub., London, 1967.

9. Svarovsky, L., Solid-Liquid Separation, 2nded., Butterworth, London, 1981.

10. Purchas, D. and Sutherland, K., Handbookof Filter Media, 2nd ed., Elsevier, N.Y.,2001.

11. Strauss, H. and Kaufman, M., Handbook forChemical Technicians, McGraw-Hill, N.Y.,1976.

12. Perry, R.H. and Green, D.W., ed., Perrys Chemi-cal Engineering Handbook, 7th ed., McGraw-Hill, N.Y., 1997.

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A Bit of Extra Lab Effort Can Prevent Grief During Scaleup