A critical examination of whether characteristic crystal images reveal the true quality of pharmaceuticals or merely present an appealing visual illusion.
Crystals are all around us – from table salt in everyday life to quartz in high-tech watches. They fascinate with their perfect, regular structure, in which atoms, ions or molecules are arranged in an exact long-range order2 .
In pharmacy, the analysis of crystal structures has long been established to guarantee the efficacy and stability of medicines. More recently, however, some providers are advertising so-called "characteristic crystal images" that are said to make visible the inner "ordering power" or even the "essence" of pharmaceuticals.
The regular, repeating pattern of atoms in a crystal lattice
Crystal structure analysis ensures drug efficacy and stability
Some claim crystal images reveal "ordering power" of medicines
What can these crystal images actually show - and what not?
A crystal is by definition a solid with a regular structure. Its building blocks are arranged in a repeating, periodic arrangement in space, known as a crystal lattice2 .
This structural order gives crystals their typical physical properties such as specific melting points, cleavage and the ability to refract light2 5 .
The same active pharmaceutical ingredient can exist in different crystal structures, a phenomenon known as polymorphism2 .
These different "modifications" can have significant effects on the efficacy of a drug. The identification and characterization of all possible polymorphs is therefore an essential step in drug development1 .
In pharmaceutical research, crystallography is crucial because many active ingredients exist in crystalline form. Precise knowledge of their crystal structure helps scientists understand and optimize properties such as solubility, stability and bioavailability6 .
Certain methods, such as the so-called "Soyana method", promise to make the quality or "ordering power" of pharmaceuticals and food visible through the observation of crystallization patterns3 .
A sample of the material is prepared, placed on a slide and dried. The resulting crystal structures are viewed under the microscope and photographed3 .
Proponents of this method claim that the resulting "crystal landscapes" reflect not only the mineral composition but also an immaterial "ordering power" or the "essence" of the material. These images are said to be "immediately and correctly interpretable by all people without training"3 .
Although the method is described as "standardized", there is often a lack of transparent, traceable protocols that guarantee independent reproducibility of the results.
The statement that the images can be interpreted without expert knowledge makes the interpretation susceptible to subjective perception and the Barnum effect.
There is no scientifically proven causal chain that explains how an "ordering power" of any kind should control the formation of specific crystal patterns in a droplet solution.
"The interpretation of crystal images as indicators of 'ordering power' lacks scientific foundation and relies on subjective perception rather than empirical evidence."
Genuine, scientifically sound research works with precise and reproducible methods. An example is the "Encapsulated Nanodroplet Crystallization" (ENaCt) method developed by researchers at the Universities of Newcastle and Durham1 .
This process allows hundreds of crystallization experiments to be carried out simultaneously with minimal sample amounts (micrograms of analyte in nanoliters of solvent)1 .
The goal is not the interpretation of an "ordering power", but the efficient cultivation of high-quality single crystals suitable for X-ray structure analysis. This analysis provides an objective, atomic image of the crystal structure1 .
Modern drug research increasingly relies on AI-based tools to accelerate development. An example is the prediction of co-crystals - crystals consisting of an active ingredient and a pharmaceutically harmless "co-former".
Co-crystals can significantly improve the solubility and thus the efficacy of a drug6 .
The AI searches through huge amounts of data for chemical structures that are likely to fit together and predicts which co-formers could be successful. This data-driven approach significantly reduces the number of laboratory experiments required and is transparent and verifiable6 .
| Feature | "Characteristic Crystal Images" | Scientific Crystallography (e.g. ENaCt) |
|---|---|---|
| Goal | Visualization of an "ordering power" or quality | Elucidation of atomic structure |
| Methodology | Microscopy of crystallization patterns | X-ray diffraction, high-throughput screening |
| Data | Visual patterns (images) | Structural data, diffraction patterns (quantifiable) |
| Interpretation | Subjective, "intuitive" | Objective, based on physical laws |
| Reproducibility | Often unclear | High, through standardized protocols |
| Tool | Function in Science | Use in Questionable Methods |
|---|---|---|
| Solvent | Used to dissolve the sample for crystal growth under controlled conditions1 | Used to prepare the sample solution; influence on pattern formation often not considered3 |
| X-ray Radiation | Directed at a single crystal; the diffraction pattern allows calculation of atomic positions1 2 | Not used |
| High-Throughput Robot | Automates the setup of hundreds of crystallization experiments with minimal sample amount1 | Not used; manual pipetting |
| Microscope | Used for initial screening of crystals, not for final structure determination | Is the main tool for generating "meaningfulness" |
| AI Algorithm | Analyzes chemical data to predict promising candidates for co-crystals6 | Not used |
The observation of crystal images can be aesthetically pleasing and awaken our fascination for the order in nature. As a scientific tool for assessing the quality or "ordering power" of a pharmaceutical, however, the so-called characteristic crystal images are not suitable.
Genuine scientific crystallography provides hard, reproducible data that are indispensable for the development of better medicines. It does not work with intuitive image interpretation, but with the precise measurement of X-ray diffractions and the use of high-throughput technologies and AI.
The critical observer should therefore not be deceived by the beauty of the images. The true "order" of a pharmaceutical is revealed not in a microscopic pattern, but in the exact, atomic structure, which eludes any intuitive observation and can only be deciphered through rigorous scientific methods.
| Aspect | Scientific Interpretation | Pseudoscientific Interpretation |
|---|---|---|
| Crystal Form | Result of crystal system, growth conditions and impurities2 | Expression of an immaterial "vital force" or "order" |
| Transparency | Physical property, dependent on purity and structural defects5 | Symbol for "purity" or "clarity" of the product |
| Complexity of Pattern | Result of overlapping crystallization nuclei and solvent effects | Indication of a "high information content" or "complexity" of the sample |