scale up of liquid and semi solid mixture

s26 Pharmaceutical Technology SCALING UP MANUFACTURING 2005 www.pharmtech.com

rocess scale-up is an increase inbatch size or production capac-ity, usually in response to in-

creased product demand, concernsabout high production costs, or anincreased need for clinical researchsupplies. Conversely, scale-down is adecrease in batch size or productiv-ity, usually in response to decreasedproduct demand. Pharmaceuticalmanufacturing scales range fromthe laboratory to the pilot plant tofull production. The transition fromone scale to another, however, isfraught with problems.

These problems include but arenot limited to dissimilar processingequipment between one scale andanother; various requirements forprocess control at different produc-tion scales; insufficient data aboutequipment performance at differentproduction scales; the complexity ofpharmaceutical processing, whichmay involve several very differentunit operations and equipment; andvariations in macroscopic and mi-croscopic properties of formulationcomponents and products at differ-ent production scales. Additional

Scale Up of Liquid andSemisolid ManufacturingProcessesLawrence H. Block

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Lawrence H. Block,PhD, is a professor ofpharmaceutics at the Schoolof Pharmacy, DuquesneUniversity, Pittsburgh, PA15282, tel. 412.396.6362, fax 412.396.5599, [email protected].

LIQUIDS AND SEMISOLIDS

The author points out somemajor obstacles to effectivescale-up and describesmethods available topharmaceutical scientistsfor addressing scalabilityissues.


complications arise from a relianceon trial-and-error methodology toresolve scale-up problems. Com-mentary about the paucity of pub-lished data relating to the scalabilityof pharmaceutical manufacturingprocesses is presented elsewhere (1).

This lack of information contin-ues to be a problem and fosters a re-liance on empiricism. Yet, changes inprocessing equipment, analytical in-strumentation, process analyticaltechnology, and computer softwarehave contributed to a research envi-ronment that facilitates scalability,particularly in the past 10 years. Onthe other hand, in an industry inwhich competitive advantages maybe gained by an easier approach toscale-up, publishing one’s achieve-ments in scalability would not nec-essarily be in a manufacturer’s bestinterests.

Process variations resulting from a change in scaleScale-up success often is thought tobe more likely if geometrically simi-lar processing equipment is used ateach manufacturing scale. Geometricsimilarity means that equipmentshape and dimensions are propor-tional from one production scale toanother. It would seem, then, thatgeometric similarity would ensureresults that are independent of scale.Equipment manufacturers often toutthe scalability of their equipment,specifically referring to the geometricsimilarity of various equipmentsizes.

Unfortunately, this claim is notnecessarily true. Although a system’s

chemical kinetics and thermo-dynamic properties are not affectedby changes in scale, many other sys-tem properties are affected. Geomet-ric similarity does not ensure me-chanical, thermal, or chemicalsimilarity in scaled systems. Phar-maceutical processes can vary withscale—even when the equipmentuses the same operating principle(e.g., a low-shear mixer) and thesame design characteristic (e.g., aplanetary mixer) and maintains geo-metric similarity—thus resulting indifferent outcomes for what appearsto be the same process.

Processes may be characterized asdependent on volume, area, orlength. For a given linear change inscale (L), the effect on area (L2) orvolume (L3) is very different. Thus, a10-fold change in linear scale resultsin a change in volume of three or-ders of magnitude and a change inarea of two orders of magnitude.Figure 1 shows the dependence ofthe area:volume (A:V) ratio and of


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A/V and V/A as a function of Scale

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Figure 1: The ratio of area to volume(A:V) and volume to area (V:A) as afunction of scale.

Pharmaceutical Technology SCALING UP MANUFACTURING 2005 s29

the V:A ratio on the linear scale. Atsmall production scales, area is moreprominent than volume. At largerproduction scales, volume is far moreprominent than area. As a result,process outcomes are often depend-ent on scale. Interfacially controlledprocesses such as heat transfer, parti-cle dispersion, or surfactant adsorp-tion at interfaces during emulsifica-tion are area-dependent processes.As scale increases, the area relative tothe volume decreases and the overallefficiency of the process can declineconsiderably.

Volume-dependent processessuch as droplet coalescence in anemulsion system or the amount ofheat generated in a system tend todominate system behavior at largerscales. Heat-exchange provisions(e.g., jacketed equipment) that areadequate at a small scale may begrossly inadequate at a larger scaleand necessitate a major change inequipment design. Thus, a problem-atic aspect of scaling up or down isthe potential for a change in the pre-dominant mechanism of a unit op-eration (e.g., mixing or dissolution)with a change in scale.

When pharmaceutical manufactur-ing operations are based almost ex-clusively on geometric similarity, at-tempts to scale up or scale down theprocess often fail because of the effectof changes in scale on the controllingmechanism(s) in a pharmaceuticalprocess. As Tatterson points out,“It isunwise to scale a process withoutknowing the controlling mechanisms.It is required that the controllingmechanism[s] be the same between

the two different scales. If there is amechanism change, then a regimechange has occurred” (2).

The importance of mixing in pharma-ceutical manufacturing. Mixing maybe the primary unit operation in agiven process; it is involved in themanufacture of virtually all liquidand semisolid pharmaceuticals. Paulet al. estimate that mixing problemsrelated to pharmaceutical processscale-up and process developmentcost the pharmaceutical industrymore than $500 million per year (3).

Given the centrality of mixing tothe processing of pharmaceuticalliquids and semisolids, the natureand design of the mixing equipmentare of the utmost importance to themanufacturing operation and prod-uct replicability from batch to batch.

Flow regimes (hydraulic condi-tions) in a pharmaceutical system un-dergoing mixing—whether driven bydynamic or static mixers—can rangefrom laminar to turbulent in variousregions of the system at the sametime.

A transitional-flow regime, inwhich flow is neither laminar norturbulent but is somewhere in be-tween, may also be present. The flowregime in the vicinity of an impelleris often turbulent, while the flowregime elsewhere in the system canbe laminar or transitional. A furtherindication of the importance of theflow regime is evident from theinput power needed per unit volumefor the scale-up of geometricallysimilar impeller-agitated tank sys-tems: for a turbulent-flow regime,power is rN3D2 (in which r is den-


sity, and N and D are the rotationalspeed of the impeller and the diame-ter of the impeller, respectively); fora laminar flow regime, power is hN2

(in which h is the viscosity) (4).Scale up of solutions. Insofar as the

scale-up of solutions is concerned,Gorsky advocates three methods:application of a power law, use of di-mensionless numbers, and the scale-of-agitation approach (5).

The power law approach uses thefollowing relationship (5):

N2 5 N1( 14 R)n [1]

in which n is the power law expo-nent and N1 and N2 are the rota-tional speeds of the impeller atscales 1 and 2, respectively. R is ageometric scaling factor such asD1T1 or D2T2 , in which D is the im-peller diameter and T is the mixingtank diameter, or Z1T1 or Z2T2, inwhich Z is the height of liquid in themixing tank. Depending on the scal-ing objective, commonly encoun-tered values encompass the range 0< n < 1. For example, for equalblend times, n 5 0; for equal masstransfer rates, n 5 2⁄3; and for equalsolids suspension, n 5 3⁄4.

The dimensionless numbersmethod such as the Reynolds number(i.e., the ratio of inertial to viscousforces in a flow),

Re 5 (D2rN 4 h)

or the Froude number (i.e.,the ratioof inertial stress to the gravitationalforce per unit area in a liquid),

Fr 5 (DN2 4 g)

are used as a means of correlating

process characteristics at variousproduction scales. D, N, and h inthese dimensionless numbers are thesame as previously defined, whereasr and g are density and gravitationalacceleration, respectively.

The scale-of-agitation approach—developed in the mid- to late-1970s(6, 7)—uses the power law relation-ship [1] in conjunction with dimen-sionless numbers and an empiricalscale-of-agitation (i.e., bulk-fluid ve-locity) to facilitate scale-up underconditions of geometric similarity.Gorsky provides a detailed reviewand application of the scale-of-agi-tation approach (5).

These methods tend to be prob-lematic once the systems deviatefrom Newtonian flow behavior andgeometric similarity. Nonetheless,Zlokarnik provides a rational basisfor the scaling of such systems byusing a rheologically appropriate di-mensionless term to compensate forthe non-Newtonian behavior ofmore-complex systems (8). The rhe-ological behavior of shear-thinning(pseudoplastic) systems may be de-scribed by the Ostwald–de Waeleequation between the shear rate ex-tremes corresponding to the zeroshear viscosity, h0, and to the infiniteshear viscosity, h`:

[2]

in which t is the shear stress, isthe rate of shear, and K and a areconstants. The ratio h:h0 correspon-ding to the ratio t:t0 would then beused to facilitate scaling.

Particularly difficult scale-up prob-lems arise with the scaling of disperse




systems because multiple, mechanisti-cally different phenomena are in-volved (e.g., coalescence, dispersion,and maintenance of particle suspen-sion). Leng and Calabrese note thedifficulties inherent in scaling up anemulsion system in which differ-ences in scale result in various pro-portions of the system behaving inboth a turbulent and a laminarmanner (9). Droplet dispersion ismore apt to occur in a turbulent-flow regime such as in a small vessel,but droplet coalescence is more aptto occur in a laminar-flow regime(e.g., in a large vessel). Not surpris-ingly, identical outcomes at two dif-ferent manufacturing scales are notreadily achieved.

Improving the likelihood of scalabilityAs Louis Pasteur is reputed to havesaid,“Chance favors only the mindthat is prepared.” The pharmaceuticaltechnologist confronted with a scalingproblem could prepare his or hermind to increase the likelihood ofsuccessful scaling of formulationcomponents and the product by:• identifying the physical and

chemical phenomena involved inthe pharmaceutical manufactur-ing process;

• understanding whether and howthese phenomena are affected bya change in scale (i.e., Are theydependent on volume, area, orlength?);

• identifying the predominant orcontrolling process mechanism;

• identifying the critical processvariables that affect scalability;

• identifying or determining thephysicochemical properties (e.g.,density, particle size, viscosity) ofthe formulation components andthe products relevant to scalability;

• using dimensional analysis to re-duce the number of variables re-quired to characterize a process asthe manufacturing scale changes;

• using software that enables the es-timation of equipment perform-ance and material characteristics.Dimensional analysis is a powerful

approach to scale-up that deserves se-rious consideration as a principalmethod of affecting equivalent resultsat various production scales (10, 11).Dimensional analysis goes beyond themere computation of dimensionlessnumbers by requiring the analysis ofa physical process and the conditionsunder which the process behaves sim-ilarly from one scale to another. Thisanalysis is necessary if the relevantphysical variables are to be describedin terms of the basic dimensions ofmass, length, time, and temperature.

Aside from preparing one’s mindto tackle a scale-up problem, experi-mental and computational methodscan have a substantial effect on theresolution of a scaling problem. Ex-perimental methods range from laboratory-scale to pilot-plant to full-scale production studies. Again, geo-metrically similar, proportionatelyscaled equipment can facilitate dataanalysis. Economies of scale are lost,of course, in a full-scale productionfacility. Such studies are often prohib-itively expensive.

On the other hand, there may bean advantage to conducting pilot-

Pharmaceutical Technology SCALING UP MANUFACTURING 2005 s33

plant or full-scale studies using modelsystems (i.e., “mock up” studies) thatbehave similarly to the pharmaceuti-cal system that will be scaled. Mock-up studies can provide valuable in-sight into size- or scale-related systembehavior without the investigator in-curring the expenses associated withthe actual formulation. Zlokarnik hasused aqueous solutions of various hy-drocolloids to simulate conditions inbiotechnology studies (8).

Today, the Internet abounds withnumerous Web sites devoted tomanufacturing process simulations,particularly those based on mixing(12, 13). Current literature hasbegun to reflect the increasing avail-ability of simulation software of var-ious types and of the increasing im-portance of pharmaceuticalengineering (14, 15).

It should no longer be necessaryfor a pharmaceutical scientist to re-sort to empiricism to resolve a scale-up problem. The likelihood of scale-up success is greater than ever beforebecause of the continued develop-ment and refinement of software forsimulating and computing fluid dy-namics in the processing of solutionsand disperse systems over a widerange of rheological conditions.Today, scale-up should be considereda challenge, not a problem.

References1. L.H. Block,“Nonparenteral Liquids and

Semisolids,” in Pharmaceutical ProcessScale-Up, M. Levin, Ed. (Marcel Dekker,New York, NY, 1st ed., 2002), pp. 57–58,89–90.

2. G.B. Tatterson, Scaleup and Design of In-dustrial Mixing Processes (McGraw Hill,

New York, NY, 1994), p. 242.3. E.L. Paul, V.A. Atiemo-Obeng, and S.M.

Kresta, Eds., Handbook of Industrial Mix-ing: Science and Practice (John Wiley &Sons, Hoboken, NJ, 2004), p. XXXV.

4. G.B. Tatterson, Scaleup and Design of In-dustrial Mixing Processes (McGraw Hill,New York, NY, 1994), p. 244.

5. I. Gorsky, “Parenteral Drug Scale-Up,”in Pharmaceutical Process Scale-Up, M.Levin, Ed. (Marcel Dekker, New York,NY, 1st ed., 2002), pp. 43–56.

6. R.W. Hicks and L.E. Gates,“Turbine Ag-itator Selection,” Paint Varnish Produc-tion 64 (5), 43–47 (1974).

7. R.W. Hicks et al., “How to Design Agi-tators for Desired Process Response,”Chem. Eng. 26 April 1976, 102–110.

8. M. Zlokarnik, “Scale-Up of ProcessesUsing Material Systems with VariablePhysical Properties,” Chem. Biochem.Enq. Q. 15 (2), 43–47 (2001).

9. D.E. Leng and R.V. Calabrese, “Immis-cible Liquid–Liquid Systems,” in Hand-book of Industrial Mixing: Science andPractice, E.L. Paul, V.A. Atiemo-Obeng,and S.M. Kresta, Eds. (John Wiley &Sons, Hoboken, NJ, 2004), pp. 639–753.

10. M. Zlokarnik, Dimensional Analysis andScale-up in Chemical Engineering(Springer-Verlag, Berlin, Germany, 1991).

11. M. Zlokarnik, “Dimensional Analysisand Scale-Up in Theory and IndustrialApplication,” in Pharmaceutical ProcessScale-Up, M. Levin, Ed. (Marcel Dekker,New York, 1st ed., 2002), pp. 1–41.

12. CFD Review, accessed 13 February 2005,http://www.cfdreview.com.

13. VisiMix 2000: Mixing Simulation forChemical & Process Engineers, accessed22 February 2005, http://www.on-line.visimix.com.

14. H.S. Pordal, C.J. Matice, and T.J. Fry,“The Role of Computational Fluid Dy-namics in the Pharmaceutical Industry,”Pharm. Technol. 26 (2), 72–79 (2002).

15. J. Kukura et al., “Understanding Phar-maceutical Flows,” Pharm. Technol. 26(10), 48–72 (2002). PT

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