Progressing drug development without fully understanding the structure and stability of polymorph variants can quickly lead to potential safety, efficacy or quality issues. Gaps in polymorph profiling can also lead to ambiguity in patent applications, which can have disastrous consequences even years into a drug product’s lifecycle. A clear understanding of an API and all its forms - through solid form analysis - could improve the chances of regulatory approval, decrease the time required to get a drug product to market, and protect potential revenues.
This guide explores the use of X-ray powder diffraction (XRPD) as a powerful tool to develop and improve pharmaceutical formulations and ensure quality standards are met throughout the drug development workflow.
For well over a century, small molecule drugs have formed the majority of pharmaceutical discoveries. Despite the emergence of novel therapeutics and delivery mechanisms, growth in ‘traditional’ pharmaceuticals continues at a CAGR of 7% and the industry is expected to be worth over $266 billion by 20271.
Recent advances in pharmaceutical research and development mean that many of the highly soluble and highly permeable drug substances in Class 1 of the Developability Classification System (DCS) have already been discovered. In fact, approximately 40% of current APIs (Active Pharmaceutical Ingredients) are poorly soluble, and this extends to around 90% of drugs in development2. Pharmaceutical organizations are now developing APIs in low solubility Classes 2 and 4. When working with these poorly soluble and often poorly permeable molecules, it is essential to carry out thorough solid form analysis to discover and properly characterize all crystalline and amorphous forms, as well as any solvates, salts and co-crystals. In this way, substances with better bioavailability can be identified.
With a full understanding of an API’s polymorphic profile, researchers can quickly develop a Quality Target Performance Profile (QTPP), and the meaningful and realistic Critical Material Attributes (CMAs) that ensure the QTPP is met (see figure 1).
![[Figure 1 WP211203-Stable-Solid-Forms-XRPD.png] Figure 1 WP211203-Stable-Solid-Forms-XRPD.png](https://dam.malvernpanalytical.com/f8fa9048-41c3-40f0-ab4e-adf600fcd036/Figure%201%20WP211203-Stable-Solid-Forms-XRPD_Original%20file.png)
Figure 1: Applying quality by design to drug product development
Progressing drug development without fully understanding the structure and stability of polymorph variants can quickly lead to potential safety, efficacy or quality issues. Gaps in polymorph profiling can also lead to ambiguity in patent applications, which can have disastrous consequences even years into a drug product’s lifecycle. A clear understanding of an API and all its forms - through solid form analysis - could improve the chances of regulatory approval, decrease the time required to get a drug product to market, and protect potential revenues.
This guide explores the use of X-ray powder diffraction (XRPD) as a powerful tool to develop and improve pharmaceutical formulations and ensure quality standards are met throughout the drug development workflow.
Quality by Design (QbD) is a concept many organizations have embedded into their drug development process. The USFDA states that QbD is “a systematic approach to development that begins with predefined objectives. It emphasizes product and process understanding and process control, based on sound science and quality risk management3.”
Put simply, QbD means being clear about what a drug product is and what it does, defining how this will be measured and then putting the checks in place to make sure that the drug product does what it is intended to do. In the drug development lifecycle, QbD is reflected in the use of solid form analysis to define the QTPP and establish the CMAs needed to demonstrate that the drug product ‘ticks all the boxes’.
The latest XRPD solid form analysis techniques provide valuable evidence to inform QTPP definition and enable researchers to:
From this data, meaningful and accurate polymorphic form CMAs can be established to ensure that a drug product meets its QTPP. Acceptance criteria are required for polymorphic forms that can then be translated into CMAs that are recognized by the International Committee for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). These CMAs can then meet the criteria identified in the ICH Q6A decision tree 4 for both drug substances and drug products4 (see Figure 2).
![[Figure 2a WP211203-Stable-Solid-Forms-XRPD.png] Figure 2a WP211203-Stable-Solid-Forms-XRPD.png](https://dam.malvernpanalytical.com/aca07107-5a1f-4367-9347-adf600fccd5a/Figure%202a%20WP211203-Stable-Solid-Forms-XRPD_Original%20file.png)
![[Figure 2b WP211203-Stable-Solid-Forms-XRPD.png] Figure 2b WP211203-Stable-Solid-Forms-XRPD.png](https://dam.malvernpanalytical.com/e2bfb031-b71a-46f7-bc5d-adf600fccd9c/Figure%202b%20WP211203-Stable-Solid-Forms-XRPD_Original%20file.png)
Figure 2: ICH Q6A decision tree 4 for the acceptance criteria for polymorphism in drug substances and drug products (from the ICH website).
To summarize the ICH 6A decision tree 4, an API’s solid form is considered a CMA if polymorphs are formed and those polymorphs have different solubility or stability to the intended API and the attributes of the polymorphs impact the safety, performance or efficacy of the API or drug product.
As a drug molecule moves from the early development phase into the clinic and towards the goal of approval and large-scale manufacturing, it becomes even more important that the solubility and stability, and therefore bioavailability, of the drug are maintained. Understanding the polymorphic behavior and structures of various forms is critical to establishing processes that will ensure API stability which, in turn, ensures that the product’s efficacy and safety profile does not change.
It’s well understood that the presence of polymorphic forms can affect the performance of an API, for better or worse, but defining polymorphs in terms of safety and efficacy is only part of the story. Polymorph detection and identification translates to real-world success or, indeed, business risk, particularly when it comes to patent applications and the protection of intellectual property (IP).
When a beneficial polymorph fails to be identified and included in a patent application, it can have disastrous effects for the originator, but creates some ripe opportunities for generics manufacturers.
In 2000, the drug Atorvastatin was released under patent as a cholesterol-lowering statin. In 2003, however, a generics company filed a patent for an effective polymorphic form that was not included in the originator’s patent. The originator embarked on a lengthy infringement case for two of its patents, but eventually lost the lawsuit. The generics company went on to manufacture and sell its polymorphic equivalent in 2011, five years before the originator’s patent expired and with first-to-file revenue in the first six months amounting to around $600 million5.
When a generics company tried to take the same stance against the gastric ulcer drug and H2 blocker, Zantac, the outcome was very different. Zantac was released by the originator in 1984 using polymorphic form 2 of the API Ranitidine. In 1998, when the patent for polymorphic form 1 expired, a generics company was the first to file. However, an investigation by the originator company discovered that the new generic contained five percent of polymorphic form 2. This small amount was enough to demonstrate infringement of the IP for polymorphic form 2 and barred the generics company from releasing its product for sale until 20026.
Moving from patents back to efficacy, polymorphic forms caused the antiviral protease inhibitor Norvir to be removed from the market in 1998. Released for the first time in 1996, Norvir (now known by the generic name Ritonavir) was shown to be effective in treating patients with human immunodeficiency virus (HIV) and Hepatitis C. However, in 1998, polymorphic form 2, created during the manufacturing process, was shown to be less bio-soluble and therefore less effective, limiting the efficacy of the drug and creating lasting problems for patients receiving this treatment. The drug was temporarily removed from the market until the manufacturing issues were remedied, causing significant financial losses7.
There are, of course, many methods other than XRPD that can identify an API’s solid form; however, these traditional techniques have their limitations.
Single crystal diffraction involves mounting a large crystal of the API of interest on a goniometer, firing a narrow beam of X-rays at the sample, and recording the diffracted beams with a detector. Although single crystal diffraction is useful in determining the absolute structure of a crystal and its atomic bonds’ lengths, positions and angles, as well as crystal density and disorder, its measurement is limited to just one of these crystals. It is also a time-intensive procedure, since high-quality crystals must be of a certain size in order to be measured (ideally 150 µm -250 µm).
XRPD, on the other hand, allows bulk measurement of a powder sample, consisting of multiple smaller crystals, giving a more holistic understanding of the API of interest. The resulting diffractogram is quickly obtained and gives a fast indication of the presence of single or multiple polymorphs. In addition to the sharp peaks that indicate crystalline forms, XRPD can also reveal halos (broad signals) that indicate amorphous materials, substances that often have a higher solubility and may prove beneficial when screening for and selecting new APIs for development.
Electron diffraction (ED) hasn’t traditionally been used for the determination of crystalline structure and polymorphic forms because of the scatter effect of electrons, which makes it challenging to collect reliable data. However, advances in recent years have made the 3D or microcrystal ED techniques much more viable. When electrons interact with samples, high-resolution structures can be resolved even from very small nano-crystals. However, ED is still in its infancy; there is still limited access to equipment and expertise to make this a mainstream evaluation method, and it is currently an expensive alternative to the tried and trusted XRPD methods.
Thermal analysis techniques, such as differential scanning calorimetry (DSC) or thermogravimetric analysis (TGA) are often used to augment the information determined from XRPD.
DSC works by recording the transition temperature when an API changes its state. Since the profile is unique to each polymorphic form of an API, it can be used to determine both the presence of polymorphs and their respective quantities. This technique is useful in determining the stability of the solid form of an API, and whether changing the temperature causes an API phase transition. This information helps scientists to choose polymorphic forms that are more stable, and to set conditions for API storage and manufacturing.
TGA records mass as a result of temperature change in a controlled environment. Each form of an API will generate a different thermogram, so the technique is able to identify the presence of polymorphs. Since the thermogram will change according to the compounds present in the sample, TGA can also detect solvents or contaminants. In addition, this data shows the thermal stability of the compound, which can provide useful insight for later-stage manufacturing and storage of drug products.
Despite their utility, thermal analysis techniques do not provide information on the structure of the material in question, hence cannot be applied as single characterization techniques.
Fourier-transform infrared spectroscopy (FTIR) involves aiming a beam of infrared (IR) light at an API sample. Some of the light will be absorbed, while some passes through. Measurement of both the absorbed and transmitted light is translated into a unique ‘fingerprint’ for that substance. FTIR techniques are fast, easy to use and sensitive, and are popular choices for detecting polymorphs.
Although this is a powerful and popular technique, it is not suitable for use at elevated temperatures, as the absorption of the IR light can cause the sample to degrade. Therefore, it is not sufficient for the elucidation of all structures.
Characterization of solid forms using XRPD can sometimes hold its own challenges. The substance of interest can, for example, exhibit preferred orientation, a common effect seen in powders with crystallites of anisotropic shape, e.g., plate- or needle-like instead of cube (see Figure 3). This results in deviations of the measured reflection intensities compared to calculated patterns. To eliminate this effect, an effective and easy solution is to switch the geometry of the experiment from reflection to transmission. Even though historical validation and quality control methods have been established using reflection mode, growing acceptance and appreciation of the transmission measurement mode have been observed in recent years.
![[Figure 3a WP211203-Stable-Solid-Forms-XRPD.png] Figure 3a WP211203-Stable-Solid-Forms-XRPD.png](https://dam.malvernpanalytical.com/a40cb16e-7335-4687-b19e-adf600fccbb1/Figure%203a%20WP211203-Stable-Solid-Forms-XRPD_Original%20file.png)
![[Figure 3b WP211203-Stable-Solid-Forms-XRPD.png] Figure 3b WP211203-Stable-Solid-Forms-XRPD.png](https://dam.malvernpanalytical.com/ae4cb01d-6c16-4bcf-90ca-adf600fccc70/Figure%203b%20WP211203-Stable-Solid-Forms-XRPD_Original%20file.png)
Figure 3: Random versus preferred orientation for solid form substances.
An important element of API characterization is understanding polymorphic behavior at ambient conditions. Once the initial solid form characterization is completed, the most promising lead candidates often also undergo stability assessment. Thermal analysis techniques are a good place to start; however, they can’t extract all relevant information. Transition temperatures and energies can be elucidated from DSC measurements and TGA experiments, performed as a function of relative humidity, and these can provide insight into the formation of different hydrates. Still, insight on crystalline structures can change as a function of temperature, humidity or even time and, therefore, require in situ XRPD characterization. Increasingly, stability assessments are conducted throughout development, beginning during the preclinical development phase - this de-risks and helps secure successful completion of the development workflow8.
There is an increasing demand for APIs with improved solubility, moving away from classic crystalline compounds towards nanosuspensions (in the case of dissolution-rate-limited APIs, Class IIa) or amorphous solid dispersions (in the case of solubility-limited APIs, Class IIb). In order to characterize these novel solid forms, the following X-ray scattering techniques can be applied:
Using these technologies in combination with classic XRPD protocols provides a more complete picture of the structure and behavior of solid forms. Having this breadth of data enables pharmaceutical scientists to make well-informed and future-proof choices for API development. Less stable and, therefore, less reliable lead candidates can then be eliminated early in the development process. This saves time and cost, and ensures that consequent development follows a more secure route.
Used alone or in combination with other techniques, XRPD provides a robust way to characterize APIs at all stages of the drug development workflow. By building a complete picture of the drug profile and understanding all crystalline and amorphous forms, developers can select candidates with better stability, bioavailability and ultimately efficacy.
2. Thorsteinn Loftsson, Marcus E Brewster, Pharmaceutical applications of cyclodextrins: basic science and product development, Journal of Pharmacy and Pharmacology, Volume 62, Issue 11, November 2010, Pages 1607–1621, https://doi.org/10.1111/j.2042-7158.2010.01030.x
4. https://database.ich.org/sites/default/files/Q6A%20Decision%20Tree.pdf
6. https://casetext.com/case/glaxo-inc-v-torpharm-inc
7. https://www.cmbe.engr.uga.edu/bche4520/Other/Ch9/Bauer%202001.pdf
