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Computer Simulation Studiesand the Scientific MethodRichard L. SummersPublished online: 04 Jun 2010.

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JOURNAL OF APPLIED ANIMAL WELFARE SCIENCE, 1(2), 1 19-13 1 Copyright O 1998, Lawrence Erlbaum Associates, Inc.

Computer Simulation Studies and the Scientific Method

Richard L. Summers Department of Emergency Medicine and the Department of Physiology

University of Mississippi Medical Center

The scientific method is the formal procedure for all acceptable scientific endeavors. With this methodology, there is a continual interaction between theory, in the form of an hypothesis, and objective, experimental analysis. There is a new step in the scientific method that involves the use of computer models and simulation studies. When computer models are incorporated into hypothesis formulation, they can be used in simulation studies to test ideas before they are tried experimentally. An iterative feedback between these tests and current ideas allows for a preliminary refinement of hypotheses and development of more intelligent research protocols. In this way, computer simulation studies can serve as an intermediate step in the scientific method, reducing the number of animals used in biomedical experimenta- tion. In this article we also explore other ways that computer simulation studies could limit the use of animals in biomedical research and education.

Keywords: computer simulations, scientific method, whole animal testing

When scientists consider alternatives to traditional animal testing, they usually speak of tissue cultures, isolated organ preparations, biochemical baths, or other in vitro biosystems. Only within the last few decades have computer models had a realistic potential as an alternative to the use of animals in biomedical research (Summers & Montani, 1991b). This is largely due to the recent widespread use of computers among biological scientists and the development of more sophisticated technology, capable of high-speed computation necessary for the numerical solu- tion of complex, nonlinear biological models (Montani, Adair, Summers, Coleman, & Guyton, 1989a; Montani, Adair, Summers, Coleman, & Guyton 1989b). Al- though many scientists doubt that computer models will ever totally replace animal studies, there is a great role for this technology in modern research. By incorporating

Requests for reprints should be sent to Richard Summers, Department of Emergency Medicine, University of Mississippi Medical Center, Jackson, MS 3921-505.

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the power of computer simulation studies into the traditional structure of the scientific method, the number of animals used in biomedical experimentation will be reduced.

HISTORY OF THE SCIENTIFIC METHOD IN MEDICINE

The scientific method reached its present form in the early 17th century, when Galileo performed his classic experiments concerning the motion of falling bodies. Francis Bacon further refined the concept of this method through his writings. Both scientists broke with the Aristotelian tradition for the acquisition of knowledge by deductive reasoning, instead using an objective approach to scientific discovery. Since that time, the scientific method has become the formal procedure for all acceptable scientific endeavors and has taken the general form of: (a) observing, (b) stating a hypothesis, (c) testing a hypothesis, and (d) reaching a conclusion or refining a hypothesis. The purpose of the scientific method is to try to disprove a hypothesis (test a null hypothesis) because every fact of science is continually subject to the scrutiny of objectivity. Although this methodology has found great success in the physical sciences, it probably was not until Harvey's discovery of the circulation of blood that this approach was used in the biomedical sciences (Wilson, 1994). This is due to the apparent difficulty in stating a precise hypothesis concerning biological mechanisms.

In the physical sciences, a formal statement of hypothesis usually takes the form of a mathematical expression. When a hypothesis is successful, it becomes a theory and, in the rare case when the evidence for truth becomes overwhelming, it becomes a law. The real power of science is its abiIity to prechct the occurrence of events in an uncertain world. This is easiest to do when the theory is stated in an exact mathematical relation. Until recently, the biological sciences have relied on inexact verbal descriptions because of the complex nature of the subject. However, as computer technology has become increasingly available to life scientists, many modem biological hypotheses have taken the form of detailed mathematical models (Bassingthwaighte, 1987; Coleman, 1975; Summers & Montani, 1989; Summers & Montani, 1991d). It is fitting that in 1989,400 years after the discovery of circulation, Guyton was chosen to present the prestigious Harvey Lecture for his monumental work delineating the modem-day concepts of hemodynamics. Many of the prelimi- nary hypotheses that led to these concepts were worked out with the aid of computer models and simulation studies (Guyton, Coleman, & Granger, 1972).

STRUCTURE OF THE HYPOTHESIS

The traditional view of the scientific method is that scientists use the formal process of induction to discern facts about a particular aspect of nature and then reach conclusions about how the world around them is structured. According to this view, scientists function as data-gathering automatons who either accept or reject hy-

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COMPUTER SIMULATION STUDIES AND THE SCIENTIFIC METHOD 1 21

potheses presented based on experimental evidence. In reality, the process is more Popperian in structure, with a more artistic character and less pure formalism (Medawar, 1975). Modem scientists use imaginative approaches to the scientific method, with continuous iterative feedback loops between experiments and hy- potheses formulation (Figure 1).

In a series of pilot studies, experimentalists repeatedly test current hypotheses. Depending on the results of these studies, there is a re-evaluation and modification of theories until they are refined for formal testing. Even at this point, scientists often "return 'to the drawing board," slowly molding ideas to fit experimental observations.

Many simple questions of science have been answered, leaving only systems of enormous complexity and detail to be explored-systems in which it is often difficult to tell the difference between fact and theory (Medawar, 1975). Just as blind men, examining an elephant at different ends, can conform their beliefs of the overall structure of the great beast based on the limitations of their probing fingers, scientists structure their views around theories. This is neither right or wrong, but simply reflects the limitations of human knowledge. However, the advent of the computer can help scientists to formalize the details of the dynamic, interdependent relations of many biological systems far beyond the capabilities of human thought processes. Theories that rival the complexity of the systems under study and, therefore, the process of hypothesis formulation, take on new meaning. By mim- icking the intricate dynamics of the world in computer models, nature can be re-created in scientific "dream machines."

At this point, theory and fact merge, and knowledge and beliefs can be placed in the models themselves. This form of the scientific method has reached its pinnacle in the extremes of the physical sciences, that is, cosmology and particle physics. And, this methodology has been used in many other fields of study, from economics to anthropology (Barbujani, Sokal, & Oden, 1995). In fact, in any place

:Iteatitre refinement of hypothesis : .....................--*------m

FIGURE 1 Scheme for the scientific method incorporating feedback from experimental observations for hypothesis formulation.

Experimental - Of Conclusion

Hypothesis

Hypothesis Formulation

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in which there is a limitation in ability to acquire knowledge, the use of computer models in simulation studies represents the best bridge between knowledge and belief.

TESTING THE HYPOTHESIS: THE INTERMEDIATE STEP

There are few things in nature more complicated than biological systems. The nonlinear relations that govern their functions make them difficult to understand. Hence, the computer model, with its ability to structure high levels of detail and solve differential relations by numerical analysis, is becoming increasingly impor- tant. In the biological sciences, testing the hypothesis usually means experimenta- tion on Living creatures. Unfortunately, it also often means that the scientist must destroy the life he or she seeks to understand. In the traditional scientific method, the repeated interplay between hypothesis and experiment (as shown in Figure 1) can result in the use of many animals in pilot studies, until a formal hypothesis is secured. With the scientific method of the computer age, however, the intermediate step involves first testing hypotheses using computer models in simulation studies to ensure consistency in thinking and avoid unnecessary animal experimentation (Figure 2).

Computer models can serve to form statements of hypotheses concerning proposed mechanisms of physiological functioning and provide insight into inter- actions among physiological variables that may not be obvious otherwise. In this new process, the computer simulation studies are an intermediate step between hypotheses and experiments. Providing short, iterative feedback loops, computer studies continually refine hypotheses until optimal forms are reached-before the use of animals. Computer models allow us to predict possible toxic effects of

: Computer i : Simulation ; 1 .............. :

:/terative refinement of hypothesis : , - - - - * - - - - - - - - - * - - - - - - - - - - - - - -

- Conclusion v

FIGURE 2 Scheme for the "modem" scientific method, including a computer simulation feedback for hypothesis formulation before experimentation.

Experimental Test Of

Hypothesis

Hypothesis Fonnulation -*

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substances on systems directly and indirectly affected due to subtle interactions inherent in physiological systems. Many times, the most important side effects of a h g or agent do not concern the system specifically being treated. Without the aid of computer simulation, scientists cannot always predict which variables need to be controlled for until the experimental process has begun.

For example, in the 1980s, the scientific community was very interested in the role of the newly discovered atrial peptides in controlling arterial pressure. Numer- ous in vitro and acute, whole-animal experiments demonstrated a strong effect of peptides to cause vasodilation and natriuresis (promotion of sodium excretion) when injected into the bloodstream. The resultant reduction in blood pressure led many to hypothesize that these peptides were important in the long-term control of arterial pressure. To prove such a hypothesis would have required chronic experi- ments using conscious, instrumented animals kept in metabolic cages. At the University of Mississippi Medical Center's Department of Physiology, interplay between computer models and well-designed experiments answered some very important questions concerning these peptides without the excessive use of animal testing (Summers & Montani, 1988).

It was determined that, based on the literature describing known volumes of distribution and degradation of atrial peptides, the dosages injected in many of the acute experiments would yield blood levels far above those seen under normal physiological circumstances. Likewise, a series of computer simulation studies, helped to show that it was doubtful that the atrial peptides would have a significant physiological role in the long-term control of arterial pressure. In fact, from theoretical analysis, it appeared that only under the extremes of pathological elevations in atrial pressures would there be enough of the peptide secreted to significantly influence arterial pressure. The results of these simulation studies were published long before it was widely recognized, experimentally, that there was a limited physiologic role for the atrial peptides (Kivlighn, Lohmeier, Yang, & Shin 1990; Summers, Montani, & Coleman, 1988). However, the analysis influenced the direction of the research at the University of Mississippi Medical Center's Department of Physiology, and most of the subsequent studies concentrated on the pathological levels of the peptides (Mizelle et al., 1990).

It was also discovered that the atrial peptides came in a variety of forms with differing effects. One form of atrial natriuretic peptide (ANP) was found to have a greater peripheral vasodilatory effect, whereas others were shown to be more natriuretic. All of these peptides lowered blood pressure in acute studes. When these differing effects were tested in a computer model of atrial peptide functioning, it was shown that the fall in blood pressure, due to the vasodilatory effects, was only transient (Figure 3; Summers & Montani, 1988). However, the natriuretic effects of ANP were able to maintain the pressure at a lower level chronically. Although the results of this difference were not obvious from the acute animal studies, the models alleviated the need for experimentally studying certain forms of ANP as a long-term controller of arterial pressure.

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I 4 O r Comparison of ANP Infusions

Vasodilatory ANP Infusion

Natriuretic ANP lnfusion

Difference in Steady State I ........~.~~~ . ~............~ ~~ ~.~........~~~ .- ............ ~ ~

Time (sec)

FIGURE 3 Computer simulation study demonstrating the predicted difference in the vasodi- latory and renal effects of atrial peptides on long-term blood pressure control.

Furthermore, the simulations indicated that the natriuretic effects of ANP were of the greatest significance if they were considered long-term controllers of arterial pressure.

Although on the surface it seems that animals are the greatest beneficiaries of this scientific method in the computer age, scientists have the most to gain. With the use of these new tools of thought, imagination is the only limit. Now, any researcher in any laboratory can perform thousands of theoretical experiments and explore endless venues of ideas without the risks of purchasing costly technical equipment and the drudgery of rote data collection while testing hypotheses that may not be realistic (Summers & Montani, 1988).

COMPUTER SIMULATION STUDIES AS EXPERIMENTS

For those concerned with animal welfare, simply reducing the use of animals in laboratory experiments is not enough. The question becomes whether computer models and simulation studies can totally replace the need for animal experiments. Although there is considerable debate, most biological scientists do not believe this

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COMPUTER SIMULATION STUDIES AND THE SCIENTIFIC METHOD 1 25

is currently possible. However, the matter has not been fully explored. For a model to replace laboratory animals, it must function as the animal would, given an experimental perturbation. This is almost impossible to know a priori and is probably the major limitation in the use of computer models. But this is also an admitted major limitation for many animal models used to answer questions concerning human physiology and pathology (Pandis, Bardi, & Heim, 1994).

There is always considerable debate among experimentalists as to which animal model best exemplifies the general physiological process under study. There is no specific process in any animal model that is typical of all of nature. Nature is on a continual course of evolution and is inherently diverse. Strict adherence to the scientific method allows only objective conclusions concerning the actual species under study. There is also a statistically measurable amount of uncertainty that any single animal is representative of its own species in experimental conditions. It is a license taken with the scientific method, to extrapolate these species-specific findings to general biological principles applicable to human systems. The problem is magnified when pathophysiological processes, artificially manufactured in ani- mal models, are in question.

This is obvious in resuscitation research involving external cardiac massage. Although it is difficult to justify trying new techniques on human participants in cardiac arrest, there are no animals with comparable anatomies to adequately test different protocols of chest compression. A recent study in emergency medical literature used computer simulation studies to determine the frequency and type of compression that provides optimal blood flow in an arrested state (Babbs & Thelander, 1995). This study, which used only computer methods, has been applauded as, perhaps, the only means for determining this information (Christen- son, 1995).

Despite many problems with animal models, most scientists are not convinced that computer models offer a realistic alternative. To obtain a level of scientific confidence, computer models must show a high degree of complexity in their structure (Kootsey, 1987). The assumptions on which they are built should be clearly stated, as should the limitations of animal models. Models built on detailed first principles could have the ability to accurately represent general physiological functioning as well as animal models. The use of computer simulations as experi- ments will become more credible as more is discovered about the fundamentals of biological processes and incorporated into the models.

A transition period must occur during which the scientific community will need to be convinced of the validity of computer models and simulation studies as experimental alternatives. There must be repeated examples showing accurate prediction of experimental results, portrayal of realities, and standardization of rules and techniques for buildmg trustworthy models. Many scientists are uncertain of how to evaluate results obtained from computer simulation studies. To be convinc- ing substitutes for animal experiments, computer models must be judged as any traditional scientific method. All models and their components should be validated

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using well-established data from the literature and evaluated with traditional statistical methods using three major criteria: (a) qualitative-models must behave in the directionally appropriate manner based on what has been observed experi- mentally in the literature; (b) quantitative by steady-state models must show stability and demonstrate steady-state values approaching those seen experimen- tally; and (c) quantitative in dynamics-models must respond with directionally appropriate and reasonable quantitative accuracy during dynamic transitions.

The degree of utilization of criteria can be modified by the questions asked. Sometimes, it is enough to know the general mechanism or direction of response of a system without knowing that a model exactly predicts the amount of changes. The concept of using the literature to structure new hypotheses is exciting. There are many who believe that acquisition of knowledge is already ahead of ow ability for analysis and assimilation of meaning. Computer models and simulation studies may be a way to intelligently guide future directions of biomedical research. However, the goal of making computer modeling part of mainstream biomedical science can only be accomplished if this form of research is supported by those interested in animal welfare, who believe in this scientific method (Johns Hopkins, 1995).

OTHER ROLES FOR COMPUTER MODELS IN THE SCIENTIFIC METHOD

Although the goals of using computer simulations as experiments and incorpo- rating these models into the scientific method have yet to be realized, there are a number of roles for computer models in biomedical research today that limit the need for animal experimentation.

One of the major arguments against in vitro studies is the difficulty in under- standing how the results obtained relate to integrated organ functions of whole animals. Though in vitro techniques provide insights into the functioning of specific biological elements, the information gained is out of context to the dynamic interactions of a total animal (Summers, Hudson, & Montani, 1996). The study of whole-body physiology requires a systems analysis approach for more complete understanding. With computer models it is possible that the information obtained from in vitro studies and the theoretical considerations of those findings can be used to make implications about the whole animal. The results of in vitro experiments are first translated into dose-response or cause-effect relations at the organ or cellular level. These relations are extrapolated to the whole-animal level within detailed mathematical models. The models are then computer simulated to help predict the dynamic results of the in vitro findings in the context of the total system. For instance, if we determine from in vitro studies that a known concentration of a drug suppresses insulin release from islet cells by a certain percentage, this information can be added into our previously published model of glucose homeo-

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COMPUTER SIMULATION STUDIES AND THE SCIENTIFIC METHOD 1 27

stasis (Summers & Montani, 1989; Summers & Montani, 1991~). From the com- puter simulation (Figure 4), it is obvious that the drug in question has surprisingly little effect on the steady-state glucose concentration when compared with a system without the drug. However, if a bolus dose of glucose is introduced into the model system as a perturbation, there is an obvious difference in the dynamic tolerance of the system as demonstrated by a higher peak and wider area in the glucose time curves.

It is difficult to predict this type of result from an in vitro study alone. Computer models allow scientists who do not participate in in vivo research to translate results of in vitro studies into whole-animal meaning.

In addition, computer models can be used in organ scaling from lower to higher animals (Prothero, 1984). One of the primary reasons for using primates and other higher animals in biomedical research is their similarity to man. The further from homo sapiens phylogenetically, the less likely that traditional scaling techniques, such as extrapolation by weights or body surface areas, are valid. Some animals use different biochemical pathways from primates. Using data acquired from these sources, without additional scaling and adjusting of the data set to account for biological differences, may produce misleading results. Computer models incorpo- rating these factors, such as relative blood flows and metabolic rates, have the ability to scale organ systems according to functional mechanisms. When models are built

Effect of Drug on Glucose Tolerance 220 - -

;I

, I - 200 - I

I I without drug -

I I I I with drug -

-

,160 - a, 3 140 - 0

-

I -----------------

8oo I I I

200 400 600 800 Time (sec)

FIGURE 4 Computer simulation study demonstrating the theoretical effects of a glucose bolus on the systemic dynamics of glucose homeostasis in the presence and absence of a test drug.

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on basic, biophysical principles, the experimental observations of the effects of a perturbation on the mechanics of the system can be translated by percentages to a larger model. For example, the published model of the Starling function curve, based on the well-established biophysical parameter Emax (slope of the end systolic pressure-volume relation), can easily incorporate the results of in vitro papillary muscle studies from lower animals (Summers & Montani, 1991a; Summers & Montani, 1991d; Suga & Sagawa, 1972). This is due to the fact that the basic mechanics of the actin-myofibril interactions are similar in most mammals. The function cnrve can then be inserted into a general circulatory model to determine the effects at the systemic level. In this way, the experimental findings in smaller animals can be scaled to function in a model of a larger animal or human and then extrapolated to systemic meaning.

Another role for computer models in biomedical research is protocol develop- ment. Models can provide estimates for dosages of drugs, volumes of distribution, organ delivery rates, and other details in designing experiments. For example, a simple model of glucose homeostasis to predict the amount of glucose and insulin to be infused in studies requiring insulin clamping has been used (Summers & Montani, 1989). Using pilot protocols with actual animals to develop experimental design is wasteful and often unnecessary. Planned, whole-animal computer simu- lations can be used to test the integrity of proposed protocols and look for gaps in knowledge or problems in testing before live animals are used (Guyton et al., 1988).

In some instances, only computer models that produce projected simulations over an extended period of time can give clues to the long-term effects of a system perturbation based on information gathered in short-term experiments. Long-term studies are often difficult to perform on live animals or result in unacceptable suffering for animals. The study of chronic disease states, such as hypertension and diabetes mellitus, often require experiments that last for days or weeks. The University of Mississippi Medical Center's Department of Physiology has used a model of the long-term control of blood pressure developed by Guyton to test research ideas before they are tried on animals (Guyton, Montani, Hall, & Manning, 1988). The results of these studies are limited by the accuracy and stability of the model parameters because even small deviations can demonstrate dramatic differ- ences in long-term results.

Computer modeling can indirectly provide insight into the effects of a substance on variables of animal systems that are not readily measurable without extensive instrumentation or, perhaps, not measurable at all. In these cases, computer models can provide the best estimates of parameter values based on the known structure of a system and variable values that are measurable. A recent simulation study was carried out to determine the mechanisms involved in the development of steady- state insulin resistance in obese humans (Hall, Summers, Brands, Keen, & Alonso- Galicia, 1994). The computer model allowed dissection of the individual elements controlling fasting glucose and insulin and determined their relative importance. Such a study would be impossible to perform in animal models.

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COMPUTER SIMULATION STUDlES AND THE SCIENTIFIC METHOD 1 29

Perhaps the area in which computer models have had their greatest success is in the field of education. The classroom laboratory is where the student first experi- ences the scientific method in action. Information and ideas taught in didactic lectures are tested in the student laboratory. It has been shown that knowledge gained by students from interactive, computer-assisted learning programs that simulate experiments is as effective a learning tool as the conventional laboratory- based approach and at one fifth the cost (Dewhurst, Hardcastle, J., Hardcastle, P. T., & Stuart, 1994). A general model of cardiovascular and metabolic physiology called HUMAN has been used in education for the past 15 to 20 years (Coleman & Randall, 1983). With simulation studies, students learn physiological concepts while using their imaginations to explore a variety of experiments without the use of live animals.

DISCUSSION AND CONCLUSIONS

Contrary to popular belief, most researchers in the biological sciences are concerned with the wasteful utilization and needless suffering of animals. Problems arise when scientists try to rectify the basic philosophy of the scientific method with what appears to be constraints on the acquisition of knowledge. Modem technology, in the form of high-speed digital computers, provides a potential resolution to this conflict.

Since the beginning of scientific exploration, mathematical models have been used to put ideas into simple and exact expressions, with the ability to predict many events in an ever-changing world. The physical sciences have had enormous success using quantitative computer models to formulate concrete hypotheses. Methodologies are now being developed for using mathematical models of biologi- cal systems in computer simulation studies to explore hypotheses concerning basic physiology, pharmacology, and toxicology, and to extrapolate the findings of in vitro tissue and cell culture preparations to theoretical meaning within the context of the total animal (Summers, Hudson, & Montani, 1996; Summers & Montani, 1991b; Summers & Montani, 1991~). These models can also help scientists to prepare formal statements of hypotheses concerning proposed mechanisms of physiological functioning and when used in computer simulation studies can reveal insight into interactions among physiological variables that may not otherwise be obvious. Models used in this way can help to develop and test hypotheses concern- ing complex systems and can assist in the development of more intelligent research protocols before they are performed on live animals.

One of the major stated goals of most animal welfare organizations is to refine and reduce the number of animals used in biomedical experimentation (Johns Hopkins, 1995). Although computer simulation studies have not yet reached a level of sophistication to totally replace responsible animal research, they can serve as a means for refining experimental protocols, reducing the number of animals who must suffer.

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130 SUMMERS

Mathematical models and computer simulations are not yet a complete answer to eliminating animals from biomedical research. There are a number of theoretical and philosophical issues remaining. The gaps in understanding the detailed func- tioning of biological systems precludes the use of computer simulation methodolo- gies in some areas. In some areas, animal studies may be the only means for obtaining a complete picture at this point, particularly for parameters that are not realistically measurable or only have meaning for human systems. As the limita- tions of technology to explore biosystems through objective experimentation are reached, however, computer model theories can function as laboratories for discov- ery as they have in cosmology, particle physics, social sciences, and other areas of scientific exploration. As knowledge of biological systems progresses, computer models will become more detailed and sophisticated, providing greater insight into the future of biomedical research. It has been suggested that all grant applications and animal-use submissions include a prospective computer simulation study to test the integrity of ideas. With continuing interaction between empirical and theoretical methods, scientific goals can be carried out in biomedical research without the unnecessary suffering of animals-a moral obligation of science to animals and good scientific practice.

ACKNOWLEDGMENT

This study was supported by a grant from the National Institutes of Health (HL51971).

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