The Optimal Design of the Genetic Code



Were there no example in the world of contrivance except that of the eye, it would be alone sufficient to support the conclusion which we draw from it, as to the necessity of an intelligent Creator.

–William Paley, Natural Theology

In his classic work, Natural TheologyWilliam Paley surveyed a range of biological systems, highlighting their similarities to human-made designs. Paley noticed that human designs typically consist of various components that interact in a precise way to accomplish a purpose. According to Paley, human designs are contrivances—things produced with skill and cleverness—and they come about via the work of human agents. They come about by the work of intelligent designers. And because biological systems are contrivances, they, too, must come about via the work of a Creator.

For Paley, the pervasiveness of biological contrivances made the case for a Creator compelling. But he was especially struck by the vertebrate eye. For Paley, if the only example of a biological contrivance available to us was the eye, its sophisticated design and elegant complexity alone justify the “necessity of an intelligent creator” to explain its origin.

As a biochemist, I am impressed with the elegant designs of biochemical systems. The sophistication and ingenuity of these designs convinced me as a graduate student that life must stem from the work of a Mind. In my book The Cell’s Design, I follow in Paley’s footsteps by highlighting the eerie similarity between human designs and biochemical systems—a similarity I describe as an intelligent design pattern. Because biochemical systems conform to the intelligent design pattern, they must be the work of a Creator.

As with Paley, I view the pervasiveness of the intelligent design pattern in biochemical systems as critical to making the case for a Creator. Yet, in particular, I am struck by the design of a single biochemical system: namely, the genetic code. On the basis of the structure of the genetic code alone, I think one is justified to conclude that life stems from the work of a Divine Mind. The latest work by a team of German biochemists on the genetic code’s design convinces me all the more that the genetic code is the product of a Creator’s handiwork.1

To understand the significance of this study and the code’s elegant design, a short primer on molecular biology is in order. (For those who have a background in biology, just skip ahead to The Optimal Genetic Code.)


The “workhorse” molecules of life, proteins take part in essentially every cellular and extracellular structure and activity. Proteins are chain-like molecules folded into precise three-dimensional structures. Often, the protein’s three-dimensional architecture determines the way it interacts with other proteins to form a functional complex.

Proteins form when the cellular machinery links together (in a head-to-tail fashion) smaller subunit molecules called amino acids. To a first approximation, the cell employs 20 different amino acids to make proteins. The amino acids that make up proteins possess a variety of chemical and physical properties.


Figure 1: The Amino Acids. Image credit: Shutterstock

Each specific amino acid sequence imparts the protein with a unique chemical and physical profile along the length of its chain. The chemical and physical profile determines how the protein folds and, therefore, its function. Because structure determines the function of a protein, the amino acid sequence is key to dictating the type of work a protein performs for the cell.


The cell’s machinery uses the information harbored in the DNA molecule to make proteins. Like these biomolecules, DNA consists of chain-like structures known as polynucleotides. Two polynucleotide chains align in an antiparallel fashion to form a DNA molecule. (The two strands are arranged parallel to one another with the starting point of one strand located next to the ending point of the other strand, and vice versa.) The paired polynucleotide chains twist around each other to form the well-known DNA double helix. The cell’s machinery forms polynucleotide chains by linking together four different subunit molecules called nucleotides. The four nucleotides used to build DNA chains are adenosine, guanosine, cytidine, and thymidine, familiarly known as A, G, C, and T, respectively.


Figure 2: The Structure of DNA. Image credit: Shutterstock

As noted, DNA stores the information necessary to make all the proteins used by the cell. The sequence of nucleotides in the DNA strands specifies the sequence of amino acids in protein chains. Scientists refer to the amino-acid-coding nucleotide sequence that is used to construct proteins along the DNA strand as a gene.

The Genetic Code

A one-to-one relationship cannot exist between the 4 different nucleotides of DNA and the 20 different amino acids used to assemble polypeptides. The cell addresses this mismatch by using a code comprised of groupings of three nucleotides to specify the 20 different amino acids.

The cell uses a set of rules to relate these nucleotide triplet sequences to the 20 amino acids making up proteins. Molecular biologists refer to this set of rules as the genetic code. The nucleotide triplets, or “codons” as they are called, represent the fundamental communication units of the genetic code, which is essentially universal among all living organisms.

Sixty-four codons make up the genetic code. Because the code only needs to encode 20 amino acids, some of the codons are redundant. That is, different codons code for the same amino acid. In fact, up to six different codons specify some amino acids. Others are specified by only one codon.

Interestingly, some codons, called stop codons or nonsense codons, code no amino acids. (For example, the codon UGA is a stop codon.) These codons always occur at the end of the gene, informing the cell where the protein chain ends.

Some coding triplets, called start codons, play a dual role in the genetic code. These codons not only encode amino acids, but also “tell” the cell where a protein chain begins. For example, the codon GUG encodes the amino acid valine and also specifies the starting point of the proteins.


Figure 3: The Genetic Code. Image credit: Shutterstock

The Optimal Genetic Code

Based on visual inspection of the genetic code, biochemists had long suspected that the coding assignments weren’t haphazard—a frozen accident. Instead it looked to them like a rationale undergirds the genetic code’s architecture. This intuition was confirmed in the early 1990s. As I describe in The Cell’s Design, at that time, scientists from the University of Bath (UK) and from Princeton University quantified the error-minimization capacity of the genetic code. Their initial work indicated that the naturally occurring genetic code withstands the potentially harmful effects of substitution mutations better than all but 0.02 percent (1 out of 5,000) of randomly generated genetic codes with codon assignments different from the universal genetic code.2

Subsequent analysis performed later that decade incorporated additional factors. For example, some types of substitution mutations (called transitions) occur more frequently in nature than others (called transversions). As a case in point, an A-to-G substitution occurs more frequently than does either an A-to-C or an A-to-T mutation. When researchers included this factor into their analysis, they discovered that the naturally occurring genetic code performed better than one million randomly generated genetic codes. In a separate study, they also found that the genetic code in nature resides near the global optimum for all possible genetic codes with respect to its error-minimization capacity.3

It could be argued that the genetic code’s error-minimization properties are more dramatic than these results indicate. When researchers calculated the error-minimization capacity of one million randomly generated genetic codes, they discovered that the error-minimization values formed a distribution where the naturally occurring genetic code’s capacity occurred outside the distribution. Researchers estimate the existence of 1018 (a quintillion) possible genetic codes possessing the same type and degree of redundancy as the universal genetic code. Nearly all of these codes fall within the error-minimization distribution. This finding means that of 1018 possible genetic codes, only a few have an error-minimization capacity that approaches the code found universally in nature.

Frameshift Mutations

Recently, researchers from Germany wondered if this same type of optimization applies to frameshift mutations. Biochemists have discovered that these mutations are much more devastating than substitution mutations. Frameshift mutations result when nucleotides are inserted into or deleted from the DNA sequence of the gene. If the number of inserted/deleted nucleotides is not divisible by three, the added or deleted nucleotides cause a shift in the gene’s reading frame—altering the codon groupings. Frameshift mutations change all the original codons to new codons at the site of the insertion/deletion and onward to the end of the gene.


Figure 4: Types of Mutations. Image credit: Shutterstock

The Genetic Code Is Optimized to Withstand Frameshift Mutations

Like the researchers from the University of Bath, the German team generated 1 million random genetic codes with the same type and degree of redundancy as the genetic code found in nature. They discovered that the code found in nature is better optimized to withstand errors that result from frameshift mutations (involving either the insertion or deletion of 1 or 2 nucleotides) than most of the random genetic codes they tested.

The Genetic Code Is Optimized to Harbor Multiple Overlapping Codes

The optimization doesn’t end there. In addition to the genetic code, genes harbor other overlapping codes that independently direct the binding of histone proteins and transcription factors to DNA and dictate processes like messenger RNA folding and splicing. In 2007, researchers from Israel discovered that the genetic code is also optimized to harbor overlapping codes.4

The Genetic Code and the Case for a Creator

In The Cell’s Design, I point out that common experience teaches us that codes come from minds. By analogy, the mere existence of the genetic code suggests that biochemical systems come from a Mind. This conclusion gains considerable support based on the exquisite optimization of the genetic code to withstand errors that arise from both substitution and frameshift mutations, along with its optimal capacity to harbor multiple overlapping codes.

The triple optimization of the genetic code arises from its redundancy and the specific codon assignments. Over 1018 possible genetic codes exist and any one of them could have been “selected” for the code in nature. Yet, the “chosen” code displays extreme optimization—a hallmark feature of designed systems. As the evidence continues to mount, it becomes more and more evident that the genetic code displays an eerie perfection.5

An elegant contrivance such as the genetic code—which resides at the heart of biochemical systems and defines the information content in the cell—is truly one in a million when it comes to reasons to believe.



  1. Regine Geyer and Amir Madany Mamlouk, “On the Efficiency of the Genetic Code after Frameshift Mutations,” PeerJ 6 (2018): e4825, doi:10.7717/peerj.4825.
  2. David Haig and Laurence D. Hurst, “A Quantitative Measure of Error Minimization in the Genetic Code,” Journal of Molecular Evolution33 (1991): 412–17, doi:1007/BF02103132.
  3. Gretchen Vogel, “Tracking the History of the Genetic Code,” Science281 (1998): 329–31, doi:1126/science.281.5375.329; Stephen J. Freeland and Laurence D. Hurst, “The Genetic Code Is One in a Million,” Journal of Molecular Evolution 47 (1998): 238–48, doi:10.1007/PL00006381.; Stephen J. Freeland et al., “Early Fixation of an Optimal Genetic Code,” Molecular Biology and Evolution 17 (2000): 511–18, doi:10.1093/oxfordjournals.molbev.a026331.
  4. Shalev Itzkovitz and Uri Alon, “The Genetic Code Is Nearly Optimal for Allowing Additional Information within Protein-Coding Sequences,” Genome Research(2007): advanced online, doi:10.1101/gr.5987307.
  5. In The Cell’s Design, I explain why the genetic code cannot emerge through evolutionary processes, reinforcing the conclusion that the cell’s information systems—and hence, life—must stem from the handiwork of a Creator.
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The Multiplexed Design of Neurons



In 1910, Major General George Owen Squier developed a technique to increase the efficiency of data transmission along telephone lines that is still used today in telecommunications and computer networks. This technique, called multiplexing, allows multiple signals to be combined and transmitted along a single cable, making it possible to share a scarce resource (available phone lines, in Squier’s day).

Today, there are a number of ways to carry out multiplexing. One of them is called time-division multiplexing. While other forms of multiplexing can be used for analog data, this technique can only be applied to digital data. Data is transmitted as a collection of bits along a single channel separated by a time interval that allows the data groups to be directed to the appropriate receiver.

Researchers from Duke University have discovered that neurons employ time-division multiplexing to transmit multiple electrical signals along a single axon.1 The remarkable similarity between data transmission techniques used by neurons and telecommunication systems and computer networks is provocative. It can also be marshaled to add support to the revitalized Watchmaker argument for God’s existence and role in the origin and design of life.

A brief primer on neurons will help us better appreciate the work of the Duke research team.


The primary component of the nervous system (the brain, spinal cord, and the peripheral system of nerves), neurons are electrically excitable cells that rely on electrochemical processes to receive and send electrical signals. By connecting to each other through specialized structures called synapses, neurons form pathways that transmit information throughout the nervous system.

Neurons consist of the soma or cell body, along with several outward extending projections called dendrites and axons.

multiplexed-design-of-neuronsImage credit: Wikipedia

Dendrites are “tree-like” projections that extend from the soma into the synaptic space. Receptors on the surface of dendrites bind neurotransmitters deposited by adjacent neurons in the synapse. These binding events trigger an electrical signal that travels along the length of the dendrites to the soma. However, axons conduct electrical impulses away from the soma toward the synapse, where this signal triggers the release of neurotransmitters into the extracellular medium, initiating electrical activity in the dendrites of adjacent neurons.

Sensory Neurons

In the world around us, many things happen at the same time. And we need to be aware of all of these events. Sensory neurons react to stimuli, communicating information about the environment to our brains. Many different types of sensory neurons exist, making possible our sense of sight, smell, taste, hearing, touch, and temperature. These sensory neurons have to be broadly tuned and may have to respond to more than one environmental stimulus at the same time. An example of this scenario would be carrying on a conversation with a friend at an outdoor café while the sounds of the city surround us.

The Duke University researchers wanted to understand the mechanism neurons employ when they transmit information about two or more environmental stimuli at the same time. To accomplish this, the scientists trained two macaques (monkeys) to look in the direction of two distinct sounds produced at two different locations in the room. After achieving this step, the researchers planted electrodes into the inferior colliculus of the monkeys’ brains and used these electrodes to record the activity of single neurons as the monkeys responded to auditory stimuli. The researchers discovered that each sound produced a unique firing rate along single neurons and that when the two sounds were presented at the same time, the neuron transmitting the electrical signals alternated back and forth between the two firing rates. In other words, the neurons employed time-division multiplexing to transmit the two signals.

Neuron Multiplexing and the Case for Creation

The capacity of neurons to multiplex signals generated by environmental stimuli exemplifies the elegance and sophistication of biological designs. And it is discoveries such as these that compel me to believe that life must stem from the work of a Creator.

But the case for a Creator extends beyond the intuition of design. Discoveries like this one breathe new life into the Watchmaker argument.

British natural theologian William Paley (1743–1805) advanced this argument by pointing out that the characteristics of a watch—with the complex interaction of its precision parts for the purpose of telling time—implied the work of an intelligent designer. Paley asserted by analogy that just as a watch requires a watchmaker, so too, does life require a Creator, since organisms display a wide range of features characterized by the precise interplay of complex parts for specific purposes.

Over the centuries, skeptics have maligned this argument by claiming that biological systems only bear a superficial similarity to human designs. That is, the analogy between human designs and biological systems is weak and, therefore, undermines the conclusion that a Divine Watchmaker exits. But, as I discuss in The Cell’s Design, the discovery of molecular motors, biochemical watches, and DNA computers—biochemical complexes with machine-like characteristics—energizes the argument. These systems are identical to the highly sophisticated machines and devices we build as human designers. In fact, these biochemical systems have been directly incorporated into nanotechnologies. And, we recognize that motors and computers, not to mention watches, come from minds. So, why wouldn’t we conclude that these biochemical systems come from a mind, as well?

Analogies between human machines and biological systems are not confined to biochemical systems. We see them at the biological level as well, as the latest work by the research team from Duke University illustrates.

It is fascinating to me that as we learn more about living systems, whether at the molecular scale, the cellular level, or the systems stage, we discover more and more instances in which biological systems bear eerie similarities to human designs. This learning strengthens the Watchmaker argument and the case for a Creator.



  1. Valeria C. Caruso et al., “Single Neurons May Encode Simultaneous Stimuli by Switching between Activity Patterns,” Nature Communications 9 (2018): 2715, doi:10.1038/s41467-018-05121-8.
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Design Principles Explain Neuron Anatomy



It’s one of the classic episodes of I Love Lucy. Originally aired on September 15, 1952, the episode entitled “Job Switching” finds Lucy and Ethel working at a candy factory. They have been assigned to an assembly line, where they are supposed to pick up pieces of candy from a moving conveyor belt, wrap them, and place the candy back on the assembly line. But the conveyor belt moves too fast for Lucy and Ethel to keep up. Eventually, they both start stuffing pieces of candy into their mouths, under their hats, and in their blouses, as fast as they can as pieces of candy on the assembly line quickly move beyond their reach—a scene of comedic brilliance.

This chaotic (albeit hilarious) scene is a good analogy for how neurons would transmit electrical signals throughout the nervous system if not for the clever design of the axons that project from the nerve cell’s soma, or cell body.

The principles that undergird the design of axons were recently discovered by a team of bioengineers at the University of California, San Diego (UCSD).1 Insights such as this highlight the elegant designs that characterize biological systems—designs worthy to be called the Creator’s handiwork—no joke.


The primary component of the nervous system (the brain, spinal cord, and the peripheral system of nerves), neurons are electrically excitable cells, thanks to electrochemical processes that take place across their cell membranes. These electrochemical activities allow the cells to receive and send electrical signals. By connecting to each other through specialized structures called synapses, neurons form pathways that transmit information throughout the nervous system. Neurologists refer to these pathways as neural circuits.

The heart of a neuron is the soma or cell body. This portion of the cell harbors the nucleus. Two sets of projections emanate from the soma: dendrites and axons. Dendrites are “tree-like” projections that extend from the soma into the synaptic space. Receptors on the surface of dendrites bind neurotransmitters deposited by adjacent neurons in the synapse. These binding events trigger an electrical signal that travels along the length of the dendrites to the soma. On the other hand, axons conduct electrical impulses away from the soma toward the synapse where this signal triggers the release of neurotransmitters into the extracellular medium, initiating electrical activity in the dendrites of adjacent neurons. Many dendrites feed the soma, but the soma gives rise to only a single axon, though the axon can branch extensively for some types of nerve cells. Axons vary significantly in terms of their diameter and length. Their diameter ranges from 1 to 20 microns. Axons can be quite long, up to a meter in length.


Image: A Neuron. Image source: Wikipedia

The electrical excitability of neurons stems from the charge separation across its cell or plasma membrane that arises due to concentration differences in positively charged sodium, potassium, and calcium ions between the cell’s interior and exterior surroundings. This charge difference sets up a voltage across the membrane that is maintained by the activity of proteins embedded within the membranes called ion pumps. This voltage is called the resting potential. When the neuron binds neurotransmitters, this event triggers membrane-bound proteins called ion channels to open up, allowing ions to flow across the membrane. This causes a localized change in the membrane voltage that propagates along the length of the dendrite or axon. This propagating voltage change is called an action potential. When the action potential reaches the end of the axon, it triggers the release of neurotransmitters into the synaptic space.

Why Are Neurons the Way They Are?

The UCSD researchers wanted to understand the principles that undergird the neuron design, specifically why the length and diameter of the axons varies so much. Previous studies indicate that axons aren’t structured to minimize the use of cellular material—otherwise they wouldn’t be so long and convoluted. Nor are they structured for speed because axons don’t propagate electrical signals as fast as they could, theoretically speaking.

Even though the UCSD bioengineers adhere to the evolutionary paradigm, they were convinced that design principles must exist that explain the anatomy and physiology of neurons. From my perspective, their conviction is uncharacteristic of many life scientists because of the nature of evolutionary mechanisms (unguided, historically contingent processes that co-opt and cobble together existing designs to create new biological systems). Based on these mechanisms, there need not be any rationale for why things are the way they are. In fact, many evolutionary biologists view most biological systems as flawed, imperfect systems that are little more than kludge jobs.

But their conviction paid off. They discovered an elegant rationale that explains the variation in axon lengths.

Refraction Ratio

The UCSD investigators reasoned that the cellular architecture of axons may reflect a trade-off between (1) the speed of signal transduction along the axon, and (2) the time it takes the axon to reset the resting potential after the action potential propagates along the length of the axon and to ready the cell for the next round of neurotransmitter release.

To test this idea, the research team defined a quantity they dubbed the refraction ratio. This is the ratio of the refractory period of a neuron and the time it takes the electrical signal to transmit along the length of the axon. These researchers calculated the refraction ratio for 12,000 axon branches of rat basket cells. (These are a special type of neuron with heavily branched axons.) They found the information they needed for these calculations in the NeuroMorpho database. They determined that the average value for the refraction ratio was 0.92. The ideal value for the refraction ratio is 1.0. A value of 1.0 for the refraction ratio reflects optimal efficiency. In other words, the refraction ratio appears to be nearly optimal.

If not for this optimization, then signal transmission along axons would suffer the same fate as the pieces of candy on the assembly line manned by Lucy and Ethel. Things would become a jumbled mess along the length of the axons and at the synaptic terminus. And, if this happened, the information transmitted by the neurons would be lost.

The researchers concluded that the axon diameter—and, more importantly, its length—are varied to ensure that the refraction ratio remains as close to 1.0 as possible. This design principle explains why the shape, length, and width of axons varies so much. The reset time (refractory period) cannot be substantially altered. But the axon geometry can be altered, and this variation controls the transmission time of the electrical signal along the axon. To put it another way, axon geometry is analogous to slowing down or speeding up the conveyor belt to ensure that the candy factory workers can wrap as many pieces of candy as possible, without having to eat any or tuck them under their hats.

The Importance of Axon Geometry

The researchers from UCSD think that the design principles they have uncovered may be helpful in understanding some neurological disorders. They reason that if a disease leads to changes in neuronal anatomy, the axon geometry may no longer be optimized (causing the refraction ratio to deviate from its ideal value). This deviation will lead to loss of information when nerve cells transmit electrical signals through neural circuits, potentially contributing to the etiology of neurological diseases.

This research team also thinks that their insights might have use in computer technology. Understanding the importance of refraction ratio should benefit the design of machine-learning systems based on brain-like neural networks. At this time, the design of machine-learning systems doesn’t account for the time it takes for signals to reach neural network nodes. By incorporating this temporal parameter into the design, the researchers believe that they can dramatically improve the power of neural networks. In fact, this research team is now building new types of machine-learning architectures based on these new insights.2

Axon Geometry and the Case for Creation

The elegant, optimized, sophisticated, and ingenious design displayed by axon geometry is the type of evidence that convinced me, as an agnostic graduate student studying biochemistry, that life must stem from the work of a Creator. The designs we observe in biology (and biochemistry) are precisely the types of designs that we would expect to see if a Creator was responsible for life’s origin, history, and design.

On the other hand, evolutionary mechanisms (based on unguided, directionless processes that rely on co-opting and modifying existing designs to create biological innovation) are expected to yield biological designs that are inherently limited and flawed. For many life scientists, the varying length and meandering, convoluted paths taken by axons serve as a reminder that evolution produces imperfect designs, just good enough for survival, but nothing more.

And, in spite of this impoverished view of biology, the UCSD bioengineers were convinced that there must be a design principle that explained the variable length of axons. And herein lies the dilemma faced by many life scientists. The paradigm they embrace demands that they view biological systems as flawed and imperfect. Yet, biological systems appear to be designed for a purpose. And, hence, biologists can’t stop from using design language when they describe the structure and function of these systems. Nor can they keep themselves from seeking design principles when they study the architecture and operation of these systems. In other words, many life scientists operate as if life was the product of a Creator’s handiwork, though they might vehemently deny God’s influence in shaping biology—and even go as far as denying God’s existence. In this particular case, the commitment these researchers had to a de facto design paradigm paid off handsomely for them—and scientific advance.

The Converse Watchmaker Argument

Along these lines, it is provocative that the insights the researchers gleaned regarding axon geometry and the refraction ratio may well translate into improved designs for neural networks and machine-learning systems. The idea that biological designs can inspire engineering and technology advances makes possible a new argument for God’s existence—one I have named the converse Watchmaker argument.

The argument goes something like this: if biological designs are the work of a Creator, then these systems should be so well-designed that they can serve as engineering models and otherwise inspire the development of new technologies.

At some level, I find the converse Watchmaker argument more compelling than the classical Watchmaker analogy. Again, it is remarkable to me that biological designs can inspire engineering efforts.

It is even more astounding to think that engineers would turn to biological designs to inspire their work if biological systems were truly generated by an unguided, historically contingent process, as evolutionary biologists claim.

Using biological designs to guide engineering efforts seems to be fundamentally incompatible with an evolutionary explanation for life’s origin and history. To think otherwise is only possible after taking a few swigs of “Vitameatavegamin” mix.



  1. Francesca Puppo, Vivek George, and Gabriel A. Silva, “An Optimized Structure-Function Design Principle Underlies Efficient Signaling Dynamics in Neurons,” Scientific Reports 8 (2018): 10460, doi:10.1038/s41598-018-28527-2.
  2. Katherine Connor, “Why Are Neuron Axons Long and Spindly? Study Shows They’re Optimizing Signaling Efficiency,” UC San Diego News Center, July 11, 2018,
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Evolution’s Flawed Approach to Science



One of the things I find most troubling about the evolutionary paradigm is the view it fosters about the nature of biological systems—including human beings.

Evolution’s mechanisms, it is said, generate biological innovations by co-opting existing designs and cobbling them together to create new ones. As a result, many people in the scientific community regard biological systems as fundamentally flawed.

As biologist Ken Miller explains in an article for Technology Review:

“Evolution . . . does not produce perfection. The fact that every intermediate stage in the development of an organ must confer a selective advantage means that the simplest and most elegant design for an organ cannot always be produced by evolution. In fact, the hallmark of evolution is the modification of pre-existing structures. An evolved organism, in short, should show the tell-tale signs of this modification.1″

So, instead of regarding humans as “fearfully and wonderfully made” (as Scripture teaches), the evolutionary paradigm denigrates human beings, as a logical entailment of its mechanisms. It renders human beings as nothing more than creatures that have been cobbled together by evolutionary mechanisms.

Adding to this concern is the impact that the evolutionary paradigm has on scientific advance. Because many in the scientific community view biological systems as fundamentally flawed, they are predisposed to conclude—oftentimes, prematurely—that biological systems lack function or purpose when initial investigations into these systems fail to uncover any obvious rationale for why these systems are the way they are. And, once these investigators conclude that a biological system is flawed, the motivation to continue studying the system dissipates. Why try to understand a flawed design? Why focus attention on biological systems that lack function? Why invest research dollars studying systems that serve no purpose?

I would contend that viewing biological systems as the Creator’s handiwork provides a superior framework for promoting scientific advance, particularly when the rationale for the structure and function of a particular biological system is not apparent. If biological systems have been created, then there must be good reasons why these systems are structured and function the way they do. And this expectation drives further study of seemingly nonfunctional, purposeless systems with the full anticipation that their functional roles will eventually be uncovered.

Recent history validates the creation model approach. During the course of the last couple of decades, the scientific community has made discovery after discovery demonstrating (1) function for biological systems long thought to be useless evolutionary vestiges, or (2) an ingenious rationale for the architecture and operation of systems long regarded as flawed designs. (For examples, see the articles listed in the Resources section.)

These discoveries were made not because of the evolutionary paradigm but in spite of it.

So often, creationists and intelligent design proponents are accused of standing in the way of scientific advance. Skeptics of creation claim that if we conclude that God created biological systems, then science grinds to a halt. If God made it, then why continue to investigate the system in question?

But, I would assert that the opposite is true. The evolutionary paradigm stultifies science by viewing biological systems as flawed and vestigial. Yet, for the biological systems discussed in the articles listed in the Resources section, the view spawned by the evolutionary paradigm delayed important advances that could have been leveraged for biomedical purposes sooner, alleviating a lot of pain and suffering.

Because a creation model perspective regards designs in nature as part of God’s handiwork, it provides the motivation to keep pressing forward, seeking a rationale for systems that seemingly lack purpose. In the handful of instances in which the scientific community has adopted this mindset, it has been rewarded, paving the way for new scientific insight that leads to biomedical breakthroughs.



  1. Kenneth R. Miller, “Life’s Grand Design,” Technology Review 97 (February/March 1994): 24–32.
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