pharmaceutical technology_ a risk-based approach to product and process quality in spray drying

7/23/2014 Pharmaceutical Technology: A Risk-Based Approach to Product and Process Quality in Spray Drying

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PHOTO COURTESY OF NIRO.

May 1, 2008

A Risk-Based Approach to Product and Process Quality inSpray DryingBy Henrik Schwartzbach

Process designs and control strategies can be improved by adopting a risk-based approachto product quality. The author describes how this approach can be applied to spray-dryingoperations.

Taking a risk-based approach to product quality is an excellent way to uncoverpotential weaknesses in process designs or control strategies. A risk assessment isdifferent from an impact assessment because the former considers the severity andthe likelihood of the impact. A properly performed risk assessment is a valuable tool indesigning experiments, defining design space, and planning design-of-controlstrategy. The ultimate goal of risk assessment is not only to achieve the desiredquality, but also to produce predictable and consistent quality.

Target product quality and product-quality consistency

The target product quality in this instance may be the desired product quality for full-scale production or a quality that is sufficient for the current scale and stage of development. Product-qualityvariability is a common problem that can be difficult to solve. Product-quality risk assessment is an effectivetool to reduce product-quality variability.

Quality impact assessment

The first stage of performing a risk assessment is identifying potential hazards. A hazard is something thatinfluences the process directly or indirectly (e.g., materials of construction or instrumentation). A typical impactassessment will identify hazards, the type of hazards, and the documentation required such as material orcalibration certificates.

Impact assessments are typically designed to identify potential hazards, but not the severity or frequency ofexposure to the identified hazards. Since neither the severity nor the frequency of the hazards is identified, animpact assessment is inadequate for designing future experiments or control strategies.

Quality risk assessment

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Figure 1

Risk is a combination of the severity of exposure to a hazard and the frequency of being exposed. Being struckby lighting is a good example of a low-risk hazard. Despite the severity of the hazard, the likelihood of ithappening is small.

A product-quality risk assessment requires both product and process understanding to be performedeffectively. Consequently, it is best performed after process development has been completed. Ideally, thetarget product quality is known at that point, including the extent to which the different product-quality attributescan vary without unacceptable quality loss. The limits of acceptable variability are rarely known for all productattributes, however. A quality risk assessment can often identify the aspects of the process that require furtherinvestigation. Quality risk assessment must be included in the experimental design or receive special attentionin the control strategy.

It is important that personnel have adequate general understanding of the process type (in this case, spraydrying), especially if the process will be scaled up at a later stage.

Applying control strategy

An ideal control strategy would allow large input variation but maintain low output variability. Unfortunately,these criteria are rarely met in the real world. A good control strategy would allow some input variation,maintain low output variability, and provide early warning of deviations. The success of such a control strategyis ultimately limited to known input variation. Process analytical technology (PAT) is a valuable tool inidentifying input variation that previously was overlooked or deemed insignificant (because of multivariateeffects, for example).

The control strategy can be simplified if the product-feed variations are small, as they frequently are. In thiscase, a good control strategy is to fix the process parameters that have the greatest product-quality impact bycontrolled variations in the process parameters with the least product-quality impact.

Spray drying

In a spray dryer, a liquid feed (e.g., solution, suspension, or emulsion) is atomized into a spray of fine dropletsand suspended in gas while drying. Spray drying is a fast method of drying because of the product's largesurface area and high heat-transfer coefficients. The product's large surface area also enables drying at lowto moderate temperatures. The rapid drying and consequent fast stabilization at moderate temperatures makespray drying feasible for heat-sensitive materials.

Spray dryers must always be cleaned and sometimes sterilized. These and other subprocesses are often ascritical as the main drying process, but are not part of the assessment as described below.

Identifying the important process parameters

In a spray dryer, droplets or particles are dried while they are suspended inthe drying gas. During the drying process, heat is transferred from the dryinggas surrounding the droplets or particles, and solvent evaporates from thedroplet or particle surface into the surrounding drying gas (see Figure 1). Theprocess also involves various complex diffusion processes, most of which arespecific to the product–solvent combination used. This complexity makesliquid-feed composition an important part of early process development.Because the liquid-feed composition rarely can be used for process-controlpurposes, however, the parameters available for process control are dryingtemperature, drying-gas humidity, and droplet size.

The conditions under which the droplets are transformed into particles influence the final solvent content andthe particle morphology.

Drying temperature

In a spray dryer, it is important to distinguish between dryer-inlet temperature,product temperature, drying temperature, and dryer-outlet temperature. In a



Figure 2

Figure 3

well-designed cocurrent spray dryer, the intense mixing of spray and dryinggas results in fast cooling of the drying gas by the evaporation of solvent. Theend result is that the temperature in the drying chamber is practically equal tothe spray-dryer outlet temperature. This parity can be measured andcalculated with computational fluid-dynamic models (see Figure 2).

Because of the evaporation of solvent from the product, the droplet or producttemperature remains lower than the spray-dryer outlet temperature during theentire drying process. The droplet or product temperature also remains lower

than the spray-dryer outlet temperature in the high-temperature region at the drying-gas inlet, where the rateof evaporation is at its highest and the droplet temperature is at its lowest (i.e., approaching the wet-bulbtemperature). The product temperature at the discharge is typically between 5 and 20 °C colder than thedrying-gas temperature at the outlet.

The importance of the drying-gas temperature at the spray-dryer outlet isclearly seen in experiments where the correlation between productcharacteristics and outlet temperature is stronger than most other processvariables. The outlet's drying-gas temperature is usually fixed at a product-specific set point by a feedback control loop. The feedback loop normallyadjusts the inlet's drying-gas temperature or the liquid-feed rate to maintainthe outlet's drying-gas temperature at the set point (see Figure 3).

Drying-gas humidity

The solvent-vapor content in the drying gas is the sum of the solvent-vapor content in the inlet drying gas andthe evaporated solvent. In most applications, the evaporated solvent is the major contributor. Because theevaporation rate is proportional to the difference between the inlet and outlet drying-gas temperature, anincrease in the inlet drying-gas temperature (at constant outlet drying-gas temperature) results in an increasein drying-gas solvent-vapor content.

The control of the inlet's drying-gas temperature depends on the control strategy applied for the outlet'sdrying-gas temperature. When the outlet drying-gas feedback loop adjusts the inlet's drying-gas temperature,the fixed set point for the liquid-feed rate indirectly sets the inlet's drying-gas temperature level (see figure 3).Alternatively, a feedback loop maintains the inlet's drying-gas temperature at the set point by adjusting themain process gas heater.

The solvent-vapor content in the inlet drying gas is controlled effectively and accurately by adjusting thecondenser's outlet gas temperature (i.e., the dew point of the gas). In applications that use ambient air as thedrying gas, the condenser is replaced by a dehumidifier or sometimes completely omitted.

Droplet size

Droplet size is controlled through the atomization process as long as suspended particles in the liquid feed aresmall compared with the droplets created. Atomization is a complex but reproducible process in which dropletsize and droplet-size distribution depend mainly on the rheology of the liquid feed, the energy applied, and theliquid-feed rate. The atomization energy can be applied and controlled in various ways such as adjusting thespeed of a spinning wheel in a rotary atomizer, the flow of a gas in a two-fluid nozzle, and the liquid-feedpressure in a pressure nozzle (see Figure 3). For a given pressure nozzle and liquid feed, the liquid-feed rateand the liquid-feed pressure are mutually dependent. Either of them can be used in a feedback loop to thefeed pump to maintain constant atomization conditions and thereby constant droplet size and droplet-sizedistribution—as long as the liquid-feed rheology remains constant.

Process-gas flow rate

Spray dryers are generally designed to work correctly within a limited range of drying-gas flow rates: typically ±10–20%. The process parameters that have been selected as critical above, however (i.e., inlet's drying-gastemperature, outlet's drying-gas temperature, and feed rate), are sufficient to calculate the heat and balanceacross the system. The drying-gas flow rate is thus a dependent process parameter, not a variable process



parameter.

Though the drying-gas flow rate is a dependent process parameter, it is impractical to control it according toreal-time mass-balance and heat calculations. A simple feedback loop between a gas-flow measurement andthe main process gas fan works just as effectively. Gas-flow measurement in this case does not require anaccurate absolute measurement: a reproducible relative measurement also suffices.

Product-quality risk assessment

Assessments of risk are relative. A risk's magnitude is gauged in comparison with other risks, and "high risk" isrelative.

Process measurements and control loops. In most spray-drying applications, a strong, reproduciblecorrelation exists between product quality attributes that are influenced by the process parameters and thebasic process measurements (e.g., temperature, pressure, and flow). Basic process measurements arereliable. Regular calibration and preventive maintenance reduce the risk of deviations even further. Theundetected failure of a process measurement or control loop is not likely. Because the process parametersmust satisfy the heat and mass balance, an undetected error in one instrument would cause other processmeasurements to deviate from the normal values.

Process measurements and control loops are effective and reliable process controls and constitute a low risk.

A few spray-drying applications do not exhibit an adequately reproducible correlation between the product-quality attributes that are influenced by process parameters and the basic process measurements. In thosecases, the process measurements and control loops are not effective for controlling the process and constitutea high risk.

Variation in feed characteristics. Dried products' characteristics change with liquid-feed variations. Theprocess impact of long-term variations in feed characteristics can be difficult to evaluate because the varationsare complex and frequently multivariate. One problem is that a limited number of raw-material batches areused in product development, and some sources of variability are easily missed or deemed insignificant.

The combination of control loops that rely on constant response to constant conditions and the difficulty indetecting and analyzing variations in the liquid feed make liquid-feed variations a moderate risk.

In cases with simple liquid feeds (e.g., a solution of one simple chemical compound), the liquid-feed variationsbecome a low risk.

Mechanical errors. Mechanical failures and assembly errors (e.g., missing or damaged gaskets) may causecontamination, deposits, or malfunctions that are not readily detectable. Operator training, standard operatingprocedures, and preventive maintenance reduce the risk of error, but a high risk of mechanical errors remains.

Applying control strategy

Process measurements and control loops. The process measurements and control loops are effectiveand reliable. A real-time heat and mass-balance calculation based on the process measurements is used todetect instruments that need calibration or certain liquid-feed abnormalities.

Spray-drying applications with an inadequate correlation between product-quality attributes and the basicprocess measurements require careful reevaluation of the process design space. The lack of correlation isfrequently explained by the choice of a marginal or unsustainable operating point.

For example, an operation close to the limits for drying often results in particleagglomeration in the drying chamber and a high risk of deposits or irregularpowder discharge (see Figure 4). Furthermore, single particles rarely have thesame performance as agglomerates of the same size. The result is a poorcorrelation between atomization conditions and particle size because thedrying conditions are marginalized typically by lowering the outlet drying-gastemperature.



Figure 4

Figure 5

Fine powders and fragile particles may change size dramatically when they arecollected in a cyclone. Cyclones have a limited efficiency in collecting finepowders. As a result, a reduced particle size may appear as a reduction incyclone yield and not as the expected reduction in particle size. On the otherhand, fragile particles may break when collected in a cyclone. In extremecases, attempts to increase the particle size through changes in atomizationconditions make the particles even more fragile. Again, the result is a poorcorrelation between atomization conditions and particle size. The lack ofcorrelation appears to stem from the drying-gas flow rate. The real cause,however, is a poor choice of the cyclone for the application.

Product may change after discharge if the conditions in the product container are not compatible with theproduct. When the product changes, it reflects the process conditions in the container, not in the spray dryer.Some product characteristics to monitor are particle size (some products are likely to form lumps oragglomerate), residual moisture (reabsorption of solvent vapor because of the increase in relative humidity asthe surrounding gas cools down), amorphousness (crystal growth in products kept at temperatures aboveglass-transition temperature), and activity or impurities (product is kept at an excessively high temperature fortoo long).

Variation in feed characteristics. The process impact of long-term variations in feed characteristics can beevaluated using PAT. In line or on line liquid-feed and final-product monitoring are ideal for establishing acorrelation between feed properties and final-product properties. Unfortunately, it is time consuming to set upthe monitoring system and analyze the collected data.

A fully developed liquid-feed and product-monitoring system can be used as an advanced feed-forward orfeedback system to adjust operating parameters. Such a system can reduce the consistency requirements forthe liquid feed and, at the same time, improve the consistency of the final product.

A system with only in line or on line final-product monitoring still requires a liquid feed with a high level ofconsistency. Even though, in most cases, variability is best controlled at its source, such a system still providesbenefits in processes with a tight design space or in a development environment where real-time data allow theprocess to be adjusted quickly. The danger in such a system is when the cause of the disturbance is notknown.

The choice of measurement type and location is naturally application-dependent. An in line or on line measuring device is generally able to providesubstantially more detailed information than traditional sampling. For example,an on line particle-size measurement shows the effect of the automatedhammers on the drying chamber (see Figure 5).

Mechanical errors. Mechanical failures frequently are not part of a process-control strategy but are one of the most common reasons for processdeviations. A pressure nozzle, for example, must be clean and without leaks towork as intended. Pressure nozzles, however, often start to leak because they have been damaged, worn out,or assembled with insufficient care. The leak causes the nozzle to foul, disturb the spray, change the particlesize, create deposits, and ultimately cause a premature shutdown. Monitoring and recording nozzles with acamera provide early warnings and facilitate fault identification.

Summary

A risk-based approach to process design provides valuable insight to the areas where process design andcontrol strategy are most likely to fail. Interestingly enough, it is frequently not the high-risk areas thatpersonnel devote most of their attention to before making a risk assessment. In many cases, the most effectiveprocess monitoring is achieved though a blend of technologies.

Subprocesses such as cleaning can and should be evaluated in the same way as the main process and canbe improved by means similar to those described above.



Henrik Schwartzbach is a senior process technologist at Niro A/S GEA Pharma Systems, Gladsaxevej 305,

2860 Soeborg, Denmark, tel. +45 39 54 54 54, [email protected]

PHOTO COURTESY OF NIRO.



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