# Lactoferrin Production: A Systematic Review of the Latest Analytical Methods
## 3 Results and Discussion
### Conclusion Remarks
#### 3.1.3 Industrial-Scale Challenges  
Although the latest described methods can significantly improve Lf production, there are some limitations to implementing them on an industrial scale. Firstly, not all methods accommodate different matrices. Immunoaffinity magnetic purification used by [PERSON] et al. is limited by the pH level of the source material, thus, cannot use yogurt, which is a product with a low pH [99]. In methods using antibodies, these particles are specific to one protein. Both the Optical Biosensor Immunoassay and Isotope-Labelled Winged Peptide method require matrix-specific antibodies, which make them applicable only to one source material [98; 111]. Another issue is the need for frequent changes of either a part of the apparatus or the materials used. [PERSON] et al. used ultrafiltration and anion exchange chromatography on the DEAE Sepharose Fast Flow column to isolate and purify n-glycans (including Lf) from whey protein concentrate with effective results. Nevertheless, this process caused clogging of the membrane after long running, as a layer of gel formed, due to the effect of concentration polarisation and worsened the filtration efficiency [107]. Similarly, an aptamer affinity column used by [PERSON] et al. could be used 10 times before losing the efficiency of the process, then had to be changed [100]. In the boron-doped titania method, the sorbent lasted for 5 cycles and needed to be replaced [115], and the colloidal y-Fe2O3-DNA hybrids proposed by [PERSON] et al. for a large-scale Lf purification could only run for two cycles before replacement [102]. Some of the presented methods are still too time-consuming to be applicable for mass production. Optical Biosensor Immunoassay conducted by [PERSON] et al. required calibration before running each experiment [98]. The HPLC performed by [PERSON] et al. involved a time-consuming sample preparation, together with the Boron-doped titania method, which needed a long process of extraction and desorption of samples [111,114]. Another example was a validation process that required multiple gradient elution experiments to implement the optimisation proposed by [PERSON] et al. [101]. Due to being a novelty, some methods need very specific conditions to run effectively, which can be difficult to achieve in a large-scale production site. [PERSON] et al. proposed a very efficient method. Still, it required a simultaneous match of many variables to perform it [112]. Similarly, [PERSON] et al. had very high recovery rates, but fitting all parameters at once turned out to be impossible [101]. Mass-scale production calls for a relatively low-cost process to meet the demand of buyers, which means that the elements required have to be largely available. [PERSON] et al. came up with an innovative technique that gave effective results but needed very specific, costly elements (polystyrene latex particles coated with anti-human LF mouse monoclonal antibody) [109]. [PERSON] et al. 's impedimetric technique was also efficient, but the cost of pure gold electrodes might exceed a rational budget [110]. In the uncoated capillary electrophoresis performed by [PERSON] et al., the capillaries had to be changed, which is a high cost, considering an industrial-scale process [112]. Lastly, producers have to take the safety of the production site into account. Methods like the Heparin Affinity Extraction with HPLC/UV proposed by [PERSON] et al. can be problematic due to toxic and potentially dangerous chemicals used in the process [105]. These are the method-specific obstacles that need to be addressed before implementing on a mass scale. Current Lf determination methods are characterised by high precision, and most methods produce high-quality Lf. It is necessary to develop highly effective techniques for sample preparation, not only in the laboratory but also on an industrial scale, which may be a bigger challenge than Lf determination in samples.